10,674 Machine Learning Manager jobs in India

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Location: BangaloreKey Responsibilities

• Lead the execution of the R&D and product roadmap, leveraging industry insights and business needs to drive ML initiatives while managing team priorities and timelines.
• Collaborate with cross-functional stakeholders to ensure alignment of ML solutions with overarching business objectives, effectively communicating technical concepts to non-technical audiences.
• Oversee the development of robust APIs and microservices, ensuring smooth integration of ML models into production environments, and guide the team in building feature pipelines for model serving.
• Mentor and develop machine learning engineers, fostering a positive and productive work environment through training, guidance, and constructive feedback.
• Conduct code reviews and establish best practices to maintain high quality and performance standards while promoting adherence to version control and model governance.
• Manage and optimize end-to-end MLOps pipelines for data collection, model training, validation, and monitoring, while ensuring team collaboration and effective resource allocation.
• Drive the implementation of model compression, quantization, and distributed training techniques to enhance performance, encouraging innovative solutions from team members.
• Track key metrics and optimize deployed models to ensure ongoing effectiveness, collaborating with team members to identify improvement opportunities.
• Collaborate with cloud architects and DevOps teams to design and maintain scalable ML infrastructure, ensuring effective resource management and deployment.
• Work closely with applied scientists and analysts to transform model requirements into production-ready solutions, facilitating teamwork across departments.
• Establish and maintain monitoring and alerting systems for deployed models, ensuring prompt issue resolution while guiding the team in best practices.
• Create and uphold documentation for ML architecture and best practices to ensure knowledge sharing within the team, promoting continuous improvement.
• Stay current with advancements in ML technologies and lead ongoing enhancement initiatives within the team, encouraging team participation in the ML community.

Required Qualifications

• Bachelors/ Masters / PhD in Computer Science or related field.
• 9+ years of experience in machine learning, with a strong portfolio of deployed ML models for various use cases, including batch, streaming, and real-time.
• 3+ years of experience in people management, leading teams of 7 or more members
• Proficient in Python for model development and data manipulation, with experience in Java or Scala for building production systems.
• Familiarity with messaging queues (e.g., Kafka, SQS) and MLOps tools (e.g., MLflow, Kubeflow, Airflow).
• Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization technologies (Docker, Kubernetes).
• Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and databases (e.g., Elasticsearch, MongoDB, PostgreSQL).
• Understanding of data processing and ETL tools (e.g., Apache Spark, Kafka).
• Experience with monitoring tools like Grafana and Prometheus.
• Strong problem-solving skills and an analytical mindset.

Preferred Qualifications

• Experience managing large-scale production systems and distributed computing environments.
• Demonstrated leadership capabilities with experience mentoring and developing junior engineers, along with strong project management skills.
• An innovative mindset with a track record of developing solutions that yield significant business improvements or patents.
• A collaborative approach to working across multiple product and application teams, with excellent communication and conflict resolution skills.
• A commitment to continuous learning, sharing knowledge, and improving team practices.

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

Address

Bangalore Office 

Bagmane Solarium City, 3^rd & 4^th floors, Neon Building, Kundanahalli Colony, Brookfield, Bengaluru, Karnataka 560037

Description

:

Your day to day

Essential Responsibilities:

Design, Develop and optimize machine learning models for various applications.

Preprocess and analyze large datasets to extract meaningful insights.

Deploy ML solutions into production environments using appropriate tools and frameworks.

Collaborate with cross-functional teams to integrate ML models into products and services.

Monitor and evaluate the performance of deployed models.

Collaborate with various stakeholders to drive the right adoption and understand changing business needs

People Management Roles:

Oversee the team’s capabilities, timely deliveries and execution

Guide and mentor the team through projects and to facilitate their career growth

What do you need to bring-

Minimum Qualifications:

Minimum of 8 years of relevant work experience and a bachelor’s degree or equivalent experience.

Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.

Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Several years of experience in designing, implementing, and deploying machine learning models and scaling ML Systems

Preferred Qualification:

Preferred Qualifications:

MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree

Experience in setting up & nurturing AI / ML teams.

Experience developing machine learning models at scale from inception to business impact and designing ML pipelines, including model versioning, model deployment, model testing, and monitoring.

Subsidiary:

PayPal

Travel Percent:

0

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit .

Who We Are:

to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at .

Belonging at PayPal:  

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please .

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

Description

:

Your way to impact   

Identify AI ML opportunities and build solutions that impact the business

Explore and execute to get solid results 

Impact team, partners and business through PayPal values 

Your day to day   

In your day to day role you will

Hire and lead a team of ML scientists, drive them to innovate, help them build careers and unblock them wherever necessary

Lead ML Projects and Conduct research to identify new and innovative ML techniques.

Innovate to create efficiencies for the team and the business. 

Work closely with other engineers, analysts and leaders to implement and optimize ML models. 

Develop and implement best practices for ML model management, deployment, and monitoring.

Collaborate with other teams to ensure ML models are integrated into the product and services. 

Assist with troubleshooting and resolving technical issues. 

Responsible for documentation, project tracking, and quality controls. 

What do you need to bring-   

The ideal candidate will possess a degree in engineering, science, statistics or mathematics with strong technical background in machine learning.

We are looking for candidates who have excellent communication skills, an analytical mindset, and a passion for problem-solving.

8+ years of hands-on experience with problem-solving using Machine Learning including 2+ years of managing a team of ML scientists

Hands-on experience with Python or Java, along with relevant technologies such as Spark, Hadoop, BigQuery, SQL, is required. 

Candidates should have in-depth knowledge of machine learning algorithms, explainable AI methods, GenAI and NLP.

Experience with Cloud frameworks such as GCP, AWS is preferred.

Experience with Lending and Financial services is a plus. 

Preferred Qualification:

Subsidiary:

PayPal

Travel Percent:

0

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit .

Who We Are:

to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at .

Belonging at PayPal:  

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please .

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

Description

:

Your day to day

Essential Responsibilities:

Design, Develop and optimize machine learning models for various applications.

Preprocess and analyze large datasets to extract meaningful insights.

Deploy ML solutions into production environments using appropriate tools and frameworks.

Collaborate with cross-functional teams to integrate ML models into products and services.

Monitor and evaluate the performance of deployed models.

Collaborate with various stakeholders to drive the right adoption and understand changing business needs

People Management Roles:

Oversee the team’s capabilities, timely deliveries and execution

Guide and mentor the team through projects and to facilitate their career growth

What do you need to bring-

Minimum Qualifications:

Minimum of 8 years of relevant work experience and a bachelor’s degree or equivalent experience.

Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.

Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Several years of experience in designing, implementing, and deploying machine learning models and scaling ML Systems

Preferred Qualification:

Preferred Qualifications:

MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree

Experience in setting up & nurturing AI / ML teams.

Experience developing machine learning models at scale from inception to business impact and designing ML pipelines, including model versioning, model deployment, model testing, and monitoring.

Subsidiary:

PayPal

Travel Percent:

0

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit .

Who We Are:

to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at .

Belonging at PayPal:  

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please .

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

Description

:

Your day to day

Essential Responsibilities:

Design, Develop and optimize machine learning models for various applications.

Preprocess and analyze large datasets to extract meaningful insights.

Deploy ML solutions into production environments using appropriate tools and frameworks.

Collaborate with cross-functional teams to integrate ML models into products and services.

Monitor and evaluate the performance of deployed models.

Collaborate with various stakeholders to drive the right adoption and understand changing business needs

People Management Roles:

Oversee the team’s capabilities, timely deliveries and execution

Guide and mentor the team through projects and to facilitate their career growth

What do you need to bring-

Minimum Qualifications:

Minimum of 8 years of relevant work experience and a bachelor’s degree or equivalent experience.

Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.

Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Several years of experience in designing, implementing, and deploying machine learning models and scaling ML Systems

Preferred Qualification:

Preferred Qualifications:

MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree

Experience in setting up & nurturing AI / ML teams.

Experience developing machine learning models at scale from inception to business impact and designing ML pipelines, including model versioning, model deployment, model testing, and monitoring.

Subsidiary:

PayPal

Travel Percent:

0

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit .

Who We Are:

to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at .

Belonging at PayPal:  

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please .

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

About Us

Aarki is an AI company that builds advertising solutions to drive mobile revenue growth. We use AI to find audiences in a privacy-first world using trillions of contextual bidding signals coupled with proprietary behavioral models. Our audience engagement platform includes a full-service agency team and a Unified Creative Strategy that delivers ad creative ideation and execution. We have worked with hundreds of advertisers over 14 years and see 5M mobile ad requests per second from over 10B devices, driving performance for publishers and brands. The company is headquartered in San Francisco, CA, with offices in the United States, EMEA, and APAC.

Role Overview

We are seeking a motivated and detail-oriented Senior Manager of Machine Learning to join our team. In this role, you will lead a team responsible for designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with decision science, engineering, and analytics teams to drive impactful data science projects and contribute to innovative solutions. Join us in pushing the boundaries of AI and mobile advertising in a collaborative environment that fosters creativity and growth. We offer a competitive salary, comprehensive benefits, and significant opportunities for career advancement.

Role & Responsibilities

• Build, grow, and mentor a high-performing data science team, focusing on both technical development and long-term career growth.
• Lead the development of scalable machine learning pipelines for programmatic mobile advertising.
• Establish best practices for model deployment, monitoring, and performance evaluation.
• Own and lead process improvements across the ML lifecycle.
• Foster collaboration with teams in Bangalore and San Francisco including decision science and bidder engineering to launch models into production and run experiments.
• Drive timely delivery of projects and ensure rapid resolution of model-related issues in production environments.
• Design and maintain data pipelines to enable efficient processing of large-scale datasets for training and evaluation.
• Work cross-functionally with product managers, engineers, and business stakeholders to integrate models into production systems.
• Stay current with advancements in machine learning and apply cutting-edge techniques to improve platform capabilities.
• Drive innovation by exploring and adopting new methodologies, tools, and technologies.

Skills & Experience

• 7+ years of hands-on experience in data science, with a strong foundation in machine learning, statistics, and modeling.
• 3+ years of experience managing teams of data scientists or ML engineers.
• Proficiency in Python and SQL; experience with Spark is a plus.
• Expertise in ML libraries such as Scikit-Learn, LightGBM, TensorFlow, and PyTorch.
• Deep understanding of probability, statistical analysis, and experimental design.
• Demonstrated experience in deploying ML models into production and ensuring ongoing model observability.
• Excellent communication skills and the ability to explain complex ideas to both technical and non-technical audiences.
• Familiarity with RTB, auction theory, and high-throughput low-latency environments is a plus.

Sprinklr is a leading enterprise software company for all customer-facing functions. With advanced AI, Sprinklr's unified customer experience management (Unified-CXM) platform helps companies deliver human experiences to every customer, every time, across any modern channel. Headquartered in New York City with employees around the world, Sprinklr works with more than 1,000 of the world's most valuable enterprises - global brands like Microsoft, P&G, Samsung and more than 50% of the Fortune 100.
Learn more about our culture and how we make our employees happier through **The Sprinklr Way ( .
**Job Description**
**Job Responsibilities**
+ Collaborate with Product, Services,Engineering and Data Science teams to build and deliver AI products.
+ Connect with internal and external stakeholders to understand use cases and advise on solutions.
+ Translate complex technical concepts to non-technical stakeholders.
+ Perform and manage tasks daily including but not limited to data annotation,AI quality monitoring, andKPIs monitoring.
+ Assist in training the team on AI-specific configuration, AI model development, delivery processes, and data analysis.
+ Knowledge of office tools like Lucid Charts, Confluence, JIRA, MS Office suite to build organized professional-level documentation.
+ Understand responsibilities and priorities, sense possible pitfalls, and timely discuss them with the team.
+ Assist or co-own escalations, work on high priority incidents, collaborate and delegate tasks within the team to meet resolutions, and establish effective synergy among stakeholders.
+ Develop systems and procedures to ensure quality of delivery.
+ Understand the scope of deliveries and create collaborative delivery plans.
+ Be accountable for service delivery performance, meeting customer expectations, and aiding in driving future demand.
+ Assist in people management, including staff recruitment, performance assessmentand training.
**Preferred Qualification**
+ Full-time bachelor's or master's degree in either of the following specializations: Management/Engineering/Communication.
+ Overall, 3-5 years of experience in ML project management, AI qualitymonitoring or similar role.
+ Understanding and knowledge of Agile and Scrum processes, terminologies, and artifacts.
+ Prior experience and background in service delivery, AI quality monitoring, data annotation, KPI monitoring, data management, team management, client communication, vendor management, and documentation.
+ Awareness of ML lifecycle and workflows, from initial client consultation to final deployment.
+ Good written and verbal communication skills - Ability to create training documentation, review project documents for peers, and create custom documentation when required for a client.
+ Organizational and interpersonal skills to keep project goals clear, have timelyconnectswith internal team/clients, and ensure deliveries are checked and tested in prior.
+ Ability to collaborate - working with theManager on setting team goals, planning, and achieving them. Also, present/share newer solutions or ideas for growth and improvements in the team.
+ Taking ownership of critical incidents, coordinating with resolution parties, and establishing effective communication between stakeholders for post-incident reviews.
+ Ensuring that systems, procedures, and methodologies are in place to support outstanding service delivery.
+ Developing a deep understanding of the projects to gain insights into the scope of service delivery.
+ Taking accountability for service delivery performance, meeting customer expectations, and driving future demand.
+ Analyzing third-party as well as internal processes and creating strategies for service delivery optimization.
**Why You'll Love Sprinklr:**
We're committed to creating a culture where you feel like you belong, are happier today than you were yesterday, and your contributions matter. At Sprinklr, we passionately, genuinely care. For full-time employees, we provide a range of comprehensive health plans, leading well-being programs, and financial protection for you and your family through a range of global and localized plans throughout the world.
For more information on Sprinklr Benefits around the world, head to to browse our country-specific benefits guides.
We focus on our mission: We founded Sprinklr with one mission: to enable every organization on the planet to make their customers happier. Our vision is to be the world's most loved enterprise software company, ever.
We believe in our product: Sprinklr was built from the ground up to enable a brand's digital transformation. Its platform provides every customer-facing team with the ability to reach, engage, and listen to customers around the world. At Sprinklr, we have many of the world's largest brands as our clients, and our employees have the opportunity to work closely alongside them.
We invest in our people: At Sprinklr, we believe every human has the potential to be amazing. We empower each Sprinklrite in the journey toward achieving their personal and professional best. For wellbeing, this includes daily meditation breaks, virtual fitness, and access to Headspace. We have continuous learning opportunities available with LinkedIn Learning and more.
EEO - Our philosophy: Our goal is to ensure every employee feels like they belong and are operating in a judgment-free zone regardless of gender, race, ethnicity, age, and lifestyle preference, among others. We value and celebrate diversity and fervently believe every employee matters and should be respected and heard. We believe we are stronger when we belong because collectively, we're more innovative, creative, and successful.
Sprinklr is proud to be an equal-opportunity workplace and is an affirmative-action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. See also Sprinklr's EEO Policy and EEO is the Law.
We're excited that you're interested in joining Sprinklr!
Please check back frequently to follow up on the progress of your application and continue to update your contact information as appropriate.
Here at Sprinklr, we're on a mission to help every organization on the planet create unified experiences that make customers happier. That customer obsession mirrors our commitment to our own people - to treating them like family, and to sharing a culture that reflects our values.
Our goal is to ensure every employee feels like they belong and are operating in a judgment-free zone regardless of gender, race, ethnicity, age, and lifestyle preference, among others. We value and celebrate diversity and fervently believe every employee matters and should be respected and heard. We believe we are stronger when we belong because collectively, we're more innovative, creative, and successful.
Sprinklr is proud to be an equal employment opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
See Sprinklr's EEO Policy and Equal Employment Opportunity is the Law notice.
Sprinklr is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans during our application process. If you have a disability or special need that requires accommodations, please let us know by filling out this form ( .

**Summary:**
Meta's Enterprise Product Applied Research team is responsible for imagining and effecting what the Meta Enterprise will look like in an AI-first world. We leverage state-of-the-art AI to build transformative products that make Metamates more productive, improve the quality of their work, and equip them to do amazing things. In the process, we are continuously setting new standards for what is possible with AI and challenging the limits of the technology.
**Required Skills:**
Software Engineering Manager, Machine Learning Responsibilities:
1. Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area
2. Work with your team and cross-functional partners to define and influence strategy
3. Drive roadmap creation and execution
4. Collaborate with various functions, drive engineering initiatives and have an impact at an organizational level
5. Participate in technical design
6. Measure the impact of your team and set clear expectations and goals
7. Work effectively with cross-functional partners and stakeholders to set and achieve optimal outcomes
8. Partner with leadership to influence and drive organization design, contribution and prioritization
**Minimum Qualifications:**
Minimum Qualifications:
9. 5+ years of software engineering work experience, including hands-on technical management building large scale systems, algorithms, and toolsets within the Machine Learning domain
10. 5+ years experience coding in one of the following languages: C++, Java, Python and/or PHP
11. BS / MS in Computer Science or related discipline (In lieu of degree, 4+ years work experience)
12. Demonstrated experience recruiting and managing technical teams, including performance management
13. Be both highly technical and an effective people manager
14. Experience supporting machine learning teams
15. Be a subject matter expert in an ML domain
16. Successful candidate must remain in role in the same team in India for a minimum period of 24 months before being eligible for transfer to another role, team or location
**Industry:** Internet

About Firstsource

Firstsource Solutions Limited, an RP-Sanjiv Goenka Group company (NSE: FSL, BSE: 532809, Reuters: FISO.BO, Bloomberg: FSOL:IN), is a specialized global business process services partner, providing transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, Retail, and other diverse industries. With an established presence in the US, the UK, India, Mexico, Australia, South Africa, and the Philippines, we make it happen for our clients, solving their biggest challenges with hyper-focused, domain-centered teams and cutting-edge tech, data, and analytics. Our real-world practitioners work collaboratively to deliver future-focused outcomes.

Job Summary:

As a Machine Learning Engineer specializing in generative AI, you will be responsible for designing, developing, and deploying advanced machine learning models that generate high-quality, human-like content. You will collaborate with cross-functional teams to integrate these models into our products, enhancing their capabilities and delivering exceptional value to our clients.

Key Responsibilities:

• Develop, train, and optimize generative AI models for various applications, including text, image, and audio generation.
• Collaborate with product managers, software engineers, and data scientists to understand project requirements and deliver robust AI solutions.
• Conduct research to stay updated on the latest advancements in generative AI and apply best practices to improve model performance.
• Implement and maintain scalable machine learning pipelines for training and deploying models in production environments.
• Evaluate and fine-tune models to ensure they meet performance, accuracy, and efficiency standards.
• Perform data preprocessing, augmentation, and annotation to prepare high-quality datasets for model training.
• Troubleshoot and resolve issues related to model performance, data quality, and integration with other systems.
• Document model architecture, training processes, and performance metrics for internal and client-facing reports.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Proven experience in developing and deploying generative AI models using frameworks such as TensorFlow, PyTorch, or similar.
• Strong programming skills in Python and proficiency with machine learning libraries and tools.
• Familiarity with natural language processing (NLP), computer vision, and other relevant AI techniques.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure for model deployment and management.
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills to effectively convey technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other advanced generative models.
• Understanding of ethical considerations and bias mitigation in AI systems.
• Contributions to open-source projects or publications in relevant conferences/journals.
• Experience with MLOps practices and tools for continuous integration and deployment of machine learning models.

️ Disclaimer: Firstsource follows a fair, transparent, and merit-based hiring process. We never ask for money at any stage. Beware of fraudulent offers and always verify through our official channels or @firstsource.com email addresses.