India presents significant opportunities in machine learning, a rapidly growing field. Data science jobs, encompassing roles like data scientists, and machine learning engineers, are in high demand. These positions require skills in statistical modeling, algorithm development, and deep learning techniques. 5,247 Machine Learning jobs in India
Head of MLOps
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About Enterpret
Enterpret is at the forefront of AI-native applications, unlocking the power of customer feedback for businesses. We centralize feedback from every channel and transform it into actionable insights that drive customer-centric decisions for teams at the world's leading companies like Perplexity, Notion, Canva, and Figma. Backed by investors such as Kleiner Perkins and Peak XV, we're redefining how businesses understand and act on the voice of their customers.
About the Role
As Head of MLOps at Enterpret, you'll be responsible for how LLM models are fine-tuned, how prompts are managed, how we run evals, how we optimize for cost, and how we optimize for speed—both at the experimentation stage and in production. This is a foundational, high-ownership role where you'll work directly with the OpenAI and Anthropic teams (whom we partner with closely), as well as AWS (whom we partner with closely), to build world-class ML infrastructure.
You'll work closely with ML researchers, backend engineers, and product teams to ensure our AI systems are resilient, secure, and cost-efficient as we grow 10x. Key success metrics include improving the speed of experimentation, time to productionization, and the quality of models. You'll report directly to the CTO.
What You'll Do
- Design and evolve Enterpret's ML platform for training, serving, and retraining our encoders and LLM models using AWS/Terraform/OpenAI/Anthropic.
- Build CI/CD pipelines tailored for ML—including model versioning, testing, canary releases, rollbacks, and gated production deploys.
- Deploy and manage model serving systems for both real-time inference (e.g., tagging support tickets on the fly) and batch pipelines (e.g., analyzing historical product feedback).
- Set up observability for model performance and data drift—using Braintrust and custom alerts to catch issues before they affect customers.
- Lead incident response, root cause analysis, and postmortems for ML systems—ensuring uptime for insights that product teams rely on, alongside governance and security.
- Track and optimize cloud usage for ML workflows, making model delivery cost-aware and aligned with product usage.
- Implement governance and security across the stack—owning IAM, data access, auditability, and model explainability where needed.
- Partner with ML and product teams to productionize GenAI and AI models powering our Knowledge Graph and Adaptive Taxonomy engine, tackling problems on retrieval, encoder LLM fine-tuning, and reinforcement learning.
- Evaluate tools for model registry, feature stores, and orchestration—and build where needed to keep the feedback loop fast.
- Champion best practices in MLOps across the org—mentoring engineers and setting scalable foundations for the future.
- Act as a coach to our team of researchers who are transitioning into engineering, helping them self-serve their capabilities and self-service these tools rather than doing it yourself.
What It Takes
- A minimum of 6 years' experience in MLOps and ML infrastructure, ideally with exposure to designing, deploying, and scaling machine learning systems in fast-paced, product-driven environments such as startups or high-growth companies.
- Deep expertise with AWS (SageMaker, EC2, EKS, S3, IAM), infrastructure-as-code (Terraform), and container orchestration (Docker, Kubernetes).
- Strong Python skills, with bonus points for Go, Bash, or Rust scripting where appropriate.
- Hands-on experience with CI/CD systems like GitHub Actions, ArgoCD, or Jenkins—especially for ML model delivery.
- Proven ability to monitor and maintain production ML systems, including model drift, latency, uptime, and alerting.
- Comfort with cloud cost optimization, resource provisioning, and auto-scaling for ML-heavy environments.
- Familiarity with model serving stacks and experimentation tools (MLflow, Langsmith, etc.).
- Bonus: exposure to GenAI workflows (LangChain, vector DBs, RAG), encoder/LLM model tuning, reinforcement learning, or responsible AI practices.
- Track record of mentoring, collaborating across functions, and taking full ownership of systems in production.
- You hate repeated manual work and have a strong drive to automate everything.
- Proficiency with AI coding agents like Claude and Cursor to work multiple times more effectively than normal.
Why Enterpret
- ML at the Core: You won't be supporting ML—you'll be enabling the core product.
- High Impact, Early Ownership: Define our MLOps foundation, influence every model's path to production, and shape how product teams experience insights.
- Work With Sharp People: Collaborate with researchers, engineers, and product builders solving complex problems every week.
- Focused, Fast Environment: No heavy process—just smart, principled builders shipping high-quality infrastructure.
- Comp + Culture: Competitive salary, meaningful equity, full-stack healthcare, generous leave, and a team-first culture built on trust and ownership.
Equal Opportunities
We are an equal opportunity employer. We ensure that none of our employees or prospective employees receives less favourable treatment as a result of age, sex, disability, marital status, colour, race, religion or ethnic origin. Equally we aim to ensure that no such employee is disadvantaged by terms and conditions of employment which cannot be justified.
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Machine Learning
Posted today
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Overview:
TekWissen Group is a workforce management provider throughout India and many other countries in the world, the Client has proven expertise in ASIC design from Spec to Silicon and software development end to end.
Job Title: Machine Learning
Location: Pune
Job Type: Full Time
Work Type: Onsite
Job Description:
- The CUSTOMER Wireless Connectivity's DSP team is a highly visible team responsible for PHY layer algorithm design, digital verification, and silicon bring-up for next-gen WLAN and narrowband transceivers.
- The team is also involved in development of Machine Learning based algorithms for Wireless Applications
As part of this core team, the contractor would:
- Construct real-life setups to collect training data for ML applications and test performance in cabled and OTA environments
- Develop machine learning algorithms using python/MATLAB from concept to deployment
- Perform model tuning and simulations for performance optimization
- Deploy concepts from ML and Wireless Communication theory to develop cutting edge technology
- Collaborate with design engineers to develop area/power efficient hardware implementations and assist in verification efforts Key
Qualifications:
- 3+ years of professional programming experience in Python/MATLAB for AIML model/M.Tech/M.S/Ph.D in electrical engineering/computer science (specialization in fields related to AIML/wireless/signal processing)
- Strong analytical and problem-solving skills Exposure to machine learning libraries such as Tensorflow/Pytorch etc.
would be preferable:
- Knowledge of wireless communications and signal processing would be a plus
TekWissen Group is an equal opportunity employer supporting workforce diversity.
Machine Learning
Posted today
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Job Description
- Study and transform data science prototypes
- Design machine learning systems
- Research and implement appropriate ML algorithms and tools
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Perform statistical analysis and fine-tuning using test results
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
- Keep abreast of developments in the field
- Proven experience as a Machine Learning Engineer or similar role
- Understanding of data structures, data modeling and software architecture
- Deep knowledge of math, probability, statistics and algorithms
- Ability to write robust code in Python, Java and R
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
- Excellent communication skills
- Ability to work in a team
- Outstanding analytical and problem-solving skills
Schedule:
- Day shift
**Job Type**: Part-time
Part-time hours: 20 per week
Pay: ₹12,000.00 - ₹16,000.00 per month
Schedule:
- Day shift
Ability to commute/relocate:
- South ext part 1, Delhi - 110049, Delhi: Reliably commute or planning to relocate before starting work (required)
**Experience**:
- total work: 1 year (preferred)
**Speak with the employer**
+91
Machine Learning
Posted today
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Job Description
- Research & develop Machine Learning models for security problems, in the areas of Networking, Application & Data.
- Suggest, collect and synthesize requirements and create effective features.
Minimum Qualifications
- Minimum of 7+ years of relevant experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc.)
- Extensive experience in handling Time-series data
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Experience in working on anomaly detection
- Experience in handling structured and unstructured data.
- Strong hands-on experience with statistical packages and ML libraries (e.g. Python scikit learn, Spark MLlib, etc.)
- Experience in developing and debugging in one or more of the languages Python
Preferred Qualifications
- Experience working with relational and NoSQL/Graph databases
- Unsupervised & Deep Learning Experience
- Ability and willingness to multi-task and learn new technologies quickly
**Salary**: ₹300,000.00 - ₹600,000.00 per year
Schedule:
- Day shift
**Experience**:
- Python: 3 years (required)
- Machine learning: 3 years (required)
Ability to Commute:
- Indore, Madhya Pradesh (required)
Ability to Relocate:
- Indore, Madhya Pradesh: Relocate before starting work (required)
**Speak with the employer**
+91
Machine Learning
Posted today
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Job Description
Key Responsibilities
- Design, develop, and optimize machine learning models and algorithms.
- Implement and fine-tune deep learning models using frameworks like PyTorch and TensorFlow.
- Analyze large, complex datasets to extract insights and identify patterns.
- Develop scalable machine learning pipelines for training, validation, and deployment.
- Collaborate with cross-functional teams to integrate ML models into production systems.
- Stay up-to-date with the latest advancements in machine learning, deep learning, and AI technologies.
- Document processes and model performance to ensure reproducibility and compliance.
Format into sections and lists to improve readability
Avoid targeting specific demographics e.g. gender, nationality and age
**Requirements**:
**Requirements**:
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- 3+ years of experience in Machine learning, Deep learning, or AI tool development.
- Proficiency in Python and experience with frameworks such as PyTorch and TensorFlow.
- Solid understanding of statistical modeling, probability, and optimization techniques.
- Experience with data preprocessing, feature engineering, and handling large datasets.
- Strong problem-solving skills and attention to detail.
- Excellent communication and teamwork abilities.
- Ability to work in a fast-paced, dynamic environment and manage multiple priorities.
Machine Learning Engineer
Posted 5 days ago
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Job Description
**Location:** Hybrid
**Job Type:** Full-time
**About Us:**
Ralliant is at the forefront of leveraging data and AI technologies to drive innovation across Precision Tech Industries. We aim to solve real-world challenges by combining advanced machine learning, cloud computing, and generative AI to deliver cutting-edge solutions. We're looking for a talented and passionate **MLE** to join our dynamic team and help us continue to push the boundaries of AI.
· **Model Deployment & MLOps:**
+ Design, build, and maintain machine learning pipelines, ensuring continuous integration and deployment (CI/CD) of models in production environments.
+ Deploy machine learning models as APIs, microservices, or serverless functions for real-time inference.
+ Manage and scale machine learning workloads using Kubernetes, Docker, and cloud-based infrastructure (AWS, Azure, GCP).
· **Automation & Scripting:**
+ Automate routine tasks across the ML lifecycle (data preprocessing, model training, evaluation, deployment) using Python, Bash, and other scripting tools.
+ Implement automation for end-to-end model management and monitor pipelines for health, performance, and anomalies.
· **Cloud Platforms & Infrastructure:**
+ Utilize cloud platforms (AWS, Azure, GCP) to optimize the scalability, performance, and cost-effectiveness of ML systems.
+ Leverage Infrastructure as Code (IaC) tools like Terraform or CloudFormation to provision and manage cloud resources effectively.
· **Data Pipelines & Integration:**
+ Build and maintain robust data pipelines to streamline data ingestion, preprocessing, and feature engineering.
+ Work with both structured and unstructured data sources and databases (SQL, NoSQL) to feed data into ML models.
· **Monitoring, Logging & Troubleshooting:**
+ Set up monitoring and logging systems to track model performance, detect anomalies, and maintain system health.
+ Diagnose and resolve issues across the machine learning pipeline and deployed models.
· **Collaboration & Communication:**
+ Collaborate closely with data scientists, software engineers, and business stakeholders to ensure machine learning models meet the required business objectives and performance standards.
+ Effectively communicate complex ML concepts and technical details to non-technical stakeholders.
· **GenAI & AI Agents Expertise:**
+ Stay up to date with the latest trends in Generative AI (e.g., GPT models, Diffusion models) and AI agents, and bring this expertise into production environments.
+ Design and deploy advanced GenAI solutions, ensuring they are aligned with business needs and ethical AI principles.
· **Security & Compliance:**
+ Implement robust security measures for machine learning models and ensure compliance with relevant data protection and privacy regulations.
+ Address vulnerabilities, ensuring safe and secure deployment of models in production environments.
· **Optimization & Cost Management:**
+ Optimize machine learning resources (compute, memory, storage) to achieve high performance while minimizing operational costs.
+ Regularly review and improve the efficiency of machine learning workflows.
· **Testing & Validation:**
+ Develop and execute rigorous testing and validation strategies to ensure the reliability, accuracy, and fairness of deployed models.
+ Use automated testing frameworks to continuously validate model performance.
**Required Skills & Qualifications:**
+ **Education** : Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
+ **Experience** :
+ Proven experience (3+ years) in machine learning engineering, MLOps, or related fields.
+ Experience with deploying and managing machine learning models in production using tools like Kubernetes, Docker, and CI/CD pipelines.
+ Hands-on experience with cloud platforms (AWS, Azure, GCP) and infrastructure automation tools (Terraform, CloudFormation).
+ Strong coding experience in Python, Bash, or other scripting languages.
+ Expertise in Generative AI models (e.g., GPT, GANs) and their deployment at scale.
+ Experience working with databases (SQL, NoSQL) and building data pipelines.
+ **DevOps & CI/CD** :
+ Knowledge of DevOps tools and practices, including version control (Git), automated testing, and continuous integration/deployment.
+ **AI Agents** : Familiarity with the latest AI agent frameworks and their deployment in real-world applications.
+ **Data Science Concepts** : Solid understanding of GenAI,NLP, Computer Vision, machine learning algorithms, data structures, and model evaluation techniques.
+ **Problem-Solving** : Strong troubleshooting and debugging skills to quickly identify and fix issues within ML pipelines and deployments.
+ **Collaboration & Communication** : Excellent communication skills with the ability to work in a cross-functional team and explain technical concepts to non-technical stakeholders.
**Preferred Qualifications:**
+ Certification in Cloud Technologies (AWS, Azure, GCP) and MLOps platforms.
+ Experience with large-scale ML systems and distributed computing.
+ Understanding of ethical AI practices and AI fairness.
+ Familiarity with cutting-edge AI technologies like reinforcement learning, AI agents, and deep learning.
**Technical Skills:**
+ Proficiency in Python, R, or other relevant programming languages.
+ Strong knowledge of machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras.
+ Experience with SQL and cloud-native data processing tools (e.g., AWS Redshift, Azure Synapse, Spark).
+ Familiarity with DevOps practices and CI/CD pipelines for ML model deployment.
**Soft Skills:**
+ Strong communication skills with the ability to translate complex technical concepts into business-friendly language.
+ Problem-solving mindset, with the ability to approach challenges creatively and collaborate with diverse teams.
+ Leadership potential or experience mentoring junior team members.
**Preferred Qualifications:**
+ Certification or training in AWS (e.g., AWS Certified Machine Learning), Azure, or other cloud services.
+ Experience working with containerization technologies like Docker and Kubernetes for model deployment.
+ Exposure to the latest trends in AI ethics, explainability, and fairness.
**Company Overview:**
Join a dynamic and innovative team at Ralliant, a leader in producing high-tech measurement instruments and essential sensors. Our brands, including Tektronix, Qualitrol, Sensing Technologies and Pacific Scientific, are at the forefront of technological advancements, providing critical products that drive innovation across various industries. At Ralliant, we are committed to excellence and continuous improvement, delivering top-tier solutions that meet the evolving needs of our Operating Companies
**These are the traits we value:**
+ You are collaborative, proactive, adaptable, and gritty. You excel at facilitating and reconciling inputs across separated geo-located teams. You balance a passion for deep understanding of innovation with the ability to deliver extraordinary results.
+ Ability to Deliver Results: A track record for delivering results with concrete financial and operational objectives as well as the capacity to organize and direct a small team.
+ Entrepreneurial Attitude: A proactive outlook that provides the chutzpah needed to overcome barriers, creatively problem solve, and test conventional thinking.
+ Comfort with Ambiguity: A willingness and aptitude for spending time in and thriving with deep uncertainty and environments where there is no clear "right answer".
+ Passion for Innovation: A demonstrated interest and desire to participate in innovation through personal study, on-the-job initiative, or other endeavors.
+ Positive Outlook: A desire to look past the objections in search of the opportunity.
+ Strong Communication Skills: An ability to explain new concepts clearly and succinctly, able to negotiate and persuade others to your point of view.
+ A need for speed; demonstrated ability to make decisions quickly and to act upon them.
+ Alongside a team of entrepreneurial, high-performing, curious people, you'll deliver breakthrough solutions to drive sustainable growth for Ralliant
**Bonus or Equity**
This position is also eligible for bonus as part of the total compensation package.
**Ralliant Corporation Overview**
Ralliant, originally part of Fortive, now stands as a bold, independent public company driving innovation at the forefront of precision technology. With a global footprint and a legacy of excellence, we empower engineers to bring next-generation breakthroughs to life - faster, smarter, and more reliably. Our high-performance instruments, sensors, and subsystems fuel mission-critical advancements across industries, enabling real-world impact where it matters most. At Ralliant we're building the future, together with those driven to push boundaries, solve complex problems, and leave a lasting mark on the world.
We Are an Equal Opportunity Employer
Ralliant Corporation and all Ralliant Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Ralliant and all Ralliant Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at
**About NewCo**
**Bonus or Equity**
This position is also eligible for bonus as part of the total compensation package.
Machine Learning Engineer
Posted today
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Job Description
Designation: - ML / MLOPs Engineer
Location: - Noida (Sector- 132)
Key Responsibilities:
• Model Development & Algorithm Optimization : Design, implement, and optimize ML
models and algorithms using libraries and frameworks such as TensorFlow , PyTorch , and
scikit-learn to solve complex business problems.
• Training & Evaluation : Train and evaluate models using historical data, ensuring accuracy,
scalability, and efficiency while fine-tuning hyperparameters.
• Data Preprocessing & Cleaning : Clean, preprocess, and transform raw data into a suitable
format for model training and evaluation, applying industry best practices to ensure data
quality.
• Feature Engineering : Conduct feature engineering to extract meaningful features from data
that enhance model performance and improve predictive capabilities.
• Model Deployment & Pipelines : Build end-to-end pipelines and workflows for deploying
machine learning models into production environments, leveraging Azure Machine
Learning and containerization technologies like Docker and Kubernetes .
• Production Deployment : Develop and deploy machine learning models to production
environments, ensuring scalability and reliability using tools such as Azure Kubernetes
Service (AKS) .
• End-to-End ML Lifecycle Automation : Automate the end-to-end machine learning
lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring
seamless operations and faster model iteration.
• Performance Optimization : Monitor and improve inference speed and latency to meet real-
time processing requirements, ensuring efficient and scalable solutions.
• NLP, CV, GenAI Programming : Work on machine learning projects involving Natural
Language Processing (NLP) , Computer Vision (CV) , and Generative AI (GenAI) ,
applying state-of-the-art techniques and frameworks to improve model performance.
• Collaboration & CI/CD Integration : Collaborate with data scientists and engineers to
integrate ML models into production workflows, building and maintaining continuous
integration/continuous deployment (CI/CD) pipelines using tools like Azure DevOps , Git ,
and Jenkins .
• Monitoring & Optimization : Continuously monitor the performance of deployed models,
adjusting parameters and optimizing algorithms to improve accuracy and efficiency.
• Security & Compliance : Ensure all machine learning models and processes adhere to
industry security standards and compliance protocols , such as GDPR and HIPAA .
• Documentation & Reporting : Document machine learning processes, models, and results to
ensure reproducibility and effective communication with stakeholders.Required Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related
field.
• 3+ years of experience in machine learning operations (MLOps), cloud engineering, or
similar roles.
• Proficiency in Python , with hands-on experience using libraries such as TensorFlow ,
PyTorch , scikit-learn , Pandas , and NumPy .
• Strong experience with Azure Machine Learning services, including Azure ML Studio ,
Azure Databricks , and Azure Kubernetes Service (AKS) .
• Knowledge and experience in building end-to-end ML pipelines, deploying models, and
automating the machine learning lifecycle.
• Expertise in Docker , Kubernetes , and container orchestration for deploying machine
learning models at scale.
• Experience in data engineering practices and familiarity with cloud storage solutions like
Azure Blob Storage and Azure Data Lake .
• Strong understanding of NLP , CV , or GenAI programming, along with the ability to apply
these techniques to real-world business problems.
• Experience with Git , Azure DevOps , or similar tools to manage version control and CI/CD
pipelines.
• Solid experience in machine learning algorithms , model training , evaluation , and
hyperparameter tuning
Machine Learning Engineer
Posted today
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Company Description
Akross IT specializes in building, scaling, and deploying end-to-end AI and Machine Learning solutions that help businesses become smarter. We focus on custom AI/ML model development and AI-powered applications tailored to meet unique business needs.
Our services include full AI lifecycle management from data collection and preprocessing to model deployment and continuous monitoring. Additionally, we offer talent solutions to scale AI initiatives by leveraging skilled AI engineers, data scientists, and ML specialists.
Role Description
We are looking for a Senior Machine Learning Engineer with 5+ years of experience in developing and deploying AI/ML-powered applications. This is a full-time hybrid role based in Hyderabad, with some work-from-home flexibility.
You will play a key role in building and enhancing our SaaS platform, which will require designing, training, and deploying ML models, as well as developing intelligent AI-driven features. You will collaborate with cross-functional teams to create scalable, production-grade solutions that integrate seamlessly into our FastAPI + Python backend and React-based frontend.
Key Responsibilities:
- Design, develop, and deploy advanced machine learning models and algorithms.
- Collaborate with product and engineering teams to build AI-powered features for our SaaS platform.
- Handle the full AI lifecycle — from data acquisition and preprocessing to production deployment and performance monitoring.
- Optimize and scale ML models for high-performance real-time applications.
- Continuously research and implement the latest advancements in AI/ML to enhance platform capabilities.
- Ensure models are robust, explainable, and meet business requirements.
Qualifications & Skills:
- 5+ years of hands-on experience in building and deploying ML/AI applications in production.
- Strong foundation in Computer Science, Statistics, and Applied Mathematics.
- Proven expertise in Pattern Recognition, Neural Networks, and Algorithm Development.
- Proficiency in Python and experience with FastAPI for backend services.
- Experience integrating ML models with modern frontend frameworks (React preferred).
- Strong knowledge of model evaluation, optimization, and scaling techniques.
- Familiarity with cloud-based AI deployments (AWS, Azure, GCP).
- Excellent problem-solving, analytical, and collaboration skills.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
Nice to Have:
- Prior experience developing AI-powered SaaS products.
- Experience with MLOps tools for CI/CD, model monitoring, and automation.
- Exposure to real-time inference and large-scale data pipelines.
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Machine Learning Architect
Posted today
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Job Summary
We are looking for a highly skilled Technical Architect with expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. The ideal candidate should have experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overall experience of 9-12 years.
This role involves architecting AI/ML/GenAI-driven applications, ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams.
Key Responsibilities
Technical Leadership & Architecture
- Design and implement scalable, secure, and high-performance architectures on AWS for AI/ML applications.
- Architect multi-tenant, enterprise-grade AI/ML solutions using AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions.
- Lead full lifecycle development of AI/ML/GenAI solutions—from PoC to production—ensuring reliability and performance.
- Define and implement best practices for MLOps, DataOps, and DevOps on AWS.
AI/ML & Generative AI Expertise
- Design Conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures using models like Claude (Anthropic), Mistral, Llama, and Titan.
- Optimize LLM inference pipelines, embeddings, vector search, and hybrid retrieval strategies for AI-based applications.
- Drive ML model training, deployment, and monitoring using AWS SageMaker and AI/ML pipelines.
Cloud & Infrastructure Management
- Architect event-driven, serverless, and microservices architectures for AI/ML applications.
- Ensure high availability, disaster recovery, and cost optimization in cloud deployments.
- Implement IAM, VPC, security best practices, and compliance.
Team & Client Engagement
- Lead and mentor a team of ML engineers, Python Developer and Cloud Engineers.
- Collaborate with business stakeholders, product teams, and multiple clients to define requirements and deliver AI/ML/GenAI-driven solutions.
- Conduct technical workshops, training sessions, and knowledge-sharing initiatives.
Multi-Client & Business Strategy
- Manage multiple client engagements, delivering AI/ML/GenAI solutions tailored to their business needs.
- Define AI/ML/GenAI roadmaps, proof-of-concept strategies, and go-to-market AI solutions.
- Stay updated on cutting-edge AI advancements and drive innovation in AI/ML offerings.
Key Skills & Technologies
Cloud & DevOps
- AWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS
- MLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK)
- Security: IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito
AI/ML & GenAI
- LLMs & Generative AI: Bedrock (Claude, Mistral, Titan), OpenAI, Llama
- ML Frameworks: TensorFlow, PyTorch, LangChain, Hugging Face
- Vector DBs: OpenSearch, Pinecone, FAISS
- RAG Pipelines, Prompt Engineering, Fine-tuning
Software Architecture & Scalability
- Serverless & Microservices Architecture
- API Design & GraphQL
- Event-Driven Systems (SNS, SQS, EventBridge, Step Functions)
- Performance Optimization & Auto Scali
Machine Learning Engineer
Posted today
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Job Description
We are seeking a highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team.
You will play a key role in designing, developing and productionalizing ML applications by evaluating models, training and/or fine tuning them. You will play a crucial role in developing Gen AI based solutions for our customers. As a senior member of the team, you will take ownership of projects, collaborating with engineers and stakeholders to ensure successful project delivery.
What we're looking for:
- At least 3 years of experience in designing & building AI applications for customer and deploying them into production
- At least 5 years of Software engineering experience in building Secure, scalable and performant applications for customers.
- Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.
- Design, develop, and operationalize existing ML models by fine tuning, personalizing it.
- Evaluate machine learning models and perform necessary tuning.
- Develop prompts that instruct LLM to generate relevant and accurate responses.
- Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.
- Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.
- Hands on customer experience with RAG solution or fine tuning of LLM model.
- Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.
- Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.
- Proven experience building and deploying machine learning models in production environments for real life applications
- Good understanding of natural language processing, computer vision or other deep learning techniques.
- Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
- Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
- Excellent communication, collaboration, and problem-solving skills.
Good to Have
- Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.
- Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure.
- Experience with Amazon Lex or Google DialogFlow CX or Microsoft Copilot studio for CCAI Agent workflows
- Experience with AutoML and vision techniques.
- Master’s degree in statistics, machine learning or related fields.
Lead Machine learning
Posted 1 day ago
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Job Description
Job Title: Machine learning engineer Lead
Location: Hybrid Role / Chennai / Bangalore
Type: Fulltime with our client
Job Required Skills:
· 5+ years experience
· College degree
· Strong proficiency in Python (bonus if also have one of these Java, Scala, etc.).
· Advanced experience in SQL; Familiarity with version control tools (Git etc.).
· Understanding of statistical, machine learning and deep learning algorithms.
Ø Manage processes
Ø Has done computer science work, technology work and analysis work – needs a good blend of this
Ø Someone to actual do the work – make improvements to processes and do the work, not just suggest/talk/plan
· Experience working with big data environments using technologies such as Spark, Flink, NoSQL DB structures.
· Experience in cloud computing technologies based analytic solutions.
- · Experience building and productionizing micro-services and REST APIs.