What Jobs are available for AI Powered Applications in India?

Machine Learning OperationsPune, IndiaJR
**ML Ops Engineer**
At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things! We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.
We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose.
**HONESTY, RELIABILITY, COLLABORATION, CURIOSITY, PASSION**
At Ensono, we are building the future of managed services with **AI, automation, and human expertise working together** . Our **Envision Operating System** is designed to orchestrate predictive, zero-touch operations across mainframe, distributed, and cloud environments.
As an **MLOps Engineer** , you'll be the **guardian of the machine learning lifecycle** -making sure models built by Data Scientists and deployed by ML Engineers continue to **perform, scale, and deliver business value** in production. From monitoring drift to automating retraining, you'll own the workflows that ensure AI doesn't just launch, but lasts.
This role is perfect for engineers who thrive in the space between **data science, DevOps, and operations** . You'll build pipelines, logging frameworks, and monitoring systems that make AI reliable and explainable. Your work ensures that our **incident predictions, anomaly detections, and optimization models** are not just powerful, but **trusted by Ops teams** and cost-effective for the business.
If you're a builder who loves creating **end-to-end systems that keep AI alive and useful in the real world** , this is the role for you.
**What You Will Do:**
+ **Lifecycle Automation** - Build workflows for retraining, validation, and redeployment of models to keep them current and reliable.
+ **Monitoring & Observability** - Develop systems to track model performance, drift, cost, and reliability in production environments.
+ **Logging & Explainability** - Ensure every prediction is traceable, explainable, and auditable to build trust with Ops and clients.
+ **Performance & Cost Optimization** - Identify opportunities to improve inference performance while reducing compute/storage costs.
+ **Collaboration with AI/ML Teams** - Partner with Data Scientists and ML Engineers to translate model requirements into production-ready, maintainable workflows.
+ **Tooling & Platform Management** - Standardize and scale the use of ML platforms, frameworks, and monitoring tools across the enterprise.
**We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply.**   
**Required Skills & Experience**
+ Strong programming skills in **Python** (must-have) with knowledge of **C++ or Java** as a plus.
+ Experience with **Docker, Kubernetes, or similar orchestration platforms** .
+ Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and their production lifecycle.
+ Hands-on experience with **MLOps platforms and tools** (MLflow, Kubeflow, SageMaker, etc.).
+ Strong background in **monitoring, logging, and performance tuning** of production ML systems.
+ Exposure to **Snowflake, ServiceNow data flows, and enterprise IT operations datasets** .
+ Knowledge of cost optimization strategies for AI/ML workloads.
JR

Machine Learning EngineerPune, IndiaJR
**Machine Learning Engineer**
At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things! We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.
We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose.
**HONESTY, RELIABILITY, COLLABORATION, CURIOSITY, PASSION**
At Ensono, we're transforming into a **software-first Managed Services Provider** , where AI/ML and automation move us from reactive firefighting to **predictive, zero-touch operations** . Our **Envision Operating System** is the platform that makes this shift possible-bringing together data, intelligence, and automation across mainframe, distributed, and cloud environments.
As a **Machine Learning Engineer (ML Engineer)** , you'll be the **builder who takes models from notebooks to production systems** . You'll work side-by-side with Data Scientists to translate their predictive insights into scalable, high-performance solutions that can run reliably at enterprise scale.
This is a role for **makers** -people who thrive at the intersection of code, models, and operations. You'll design APIs, deploy services, and ensure our AI capabilities integrate seamlessly with systems like **ServiceNow** , Snowflake, and Envision. Your work ensures that **incident predictions, anomaly detections, and optimization recommendations** don't just exist in theory-they power real-time operations, reduce downtime, and drive measurable business outcomes for our clients.
If you're the kind of engineer who loves making AI _actually work in production_ and want to be part of the team that's **rewiring managed services with intelligent automation** , this role is for you.
**What You Will Do:**
+ **Model Deployment** - Productionize machine learning models built by Data Scientists, ensuring they run reliably, securely, and at scale.
+ **API & Service Development** - Design APIs and services that expose model predictions to EnvisionOS, ServiceNow, and other enterprise systems.
+ **Performance Optimization** - Tune models for latency, throughput, and cost efficiency in real-time environments.
+ **Feature Pipeline Integration** - Collaborate with Data Engineers to ensure robust feature pipelines feed models consistently and with minimal drift.
+ **Automation & Scaling** - Use containers, orchestration, and CI/CD practices to automate deployment and monitoring of models.
+ **Cross-functional Collaboration** - Work with Ops, Data Science, and MLOps to ensure models deliver actionable, explainable outcomes that drive trust and adoption.
**We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply.**   
**Required Skills & Experience**
+ Strong programming skills in **Python** (must-have) plus C, **C++, Java, Javascript** for performance-critical applications.
+ Experience with **ML frameworks** such as TensorFlow, PyTorch, or Scikit-learn.
+ Hands-on experience with **Docker, Kubernetes, or other container orchestration** tools.
+ Familiarity with **Snowflake** and data engineering workflows for integrating feature pipelines.
+ Experience deploying models in production and exposing them through **REST APIs, Flask, or Streamlit** .
+ Knowledge of SnowFlake is beneficial
+ Strong understanding of **model optimization, hyperparameter tuning, and inference performance** .
+ Experience working with **ServiceNow or IT operations datasets** is highly desirable.
**Mindset & Values**
+ **Get Stuff Done** - You take pride in moving models out of slides and into production.
+ **Builder at Heart** - You see APIs, services, and pipelines as products that should be reliable, elegant, and scalable.
+ **Impact-Oriented** - You measure success by **uptime improvements, cost savings, and real-world adoption** of AI-driven workflows.
+ **Collaborative Engineer** - You bridge the gap between Data Scientists and Ops teams, speaking both "ML" and "production."
+ **Continuous Improver** - Always looking for ways to make models faster, cheaper, and more accurate.
**Success Looks Like**
+ Models running in **production pipelines** , integrated with ServiceNow and EnvisionOS.
+ Predictions that **Ops teams trust and act on** , reducing downtime and improving MTTR.
+ Automated deployment workflows that keep models fresh, monitored, and reliable.
+ AI capabilities that scale across **mainframe, distributed, and cloud infrastructure** seamlessly.
**Why Ensono?**
Ensono is a place where we unleash Associates to Do Great Things - for our clients and for your career. This could mean achieving a professional goal, collaborating with your team on an innovative idea, learning a new skill, reaching a wellness milestone, or engaging in your community through volunteer programs. Whatever it means to you, we want Ensono to be the place where you can do great things.
We value flexibility and work-life balance. Positions that are not required to be onsite to support a client may offer the ability to work remotely or hybrid at an Ensono office location.
JR

**Job Summary**
NetApp is seeking an ML engineer to join the Data Services organization. The overarching vision of this organization is to empower organizations to effectively manage and govern their data estate and build cyber-resiliency while accelerating their digital transformation journey. To get to this vision, we will embark on an AI-first approach to build and deliver world-class suite of data services. As a key ML engineer in this initiative, the candidate will be responsible for independently deploying scalable AI/ML-based solutions, leveraging advancements in AI to solve real-world challenges in the domains of data protection and cyber-security. The candidate will possess deep expertise in using modern AI/ML systems to ship impactful products to production. This is going to be a challenging and a fun role in one of the most exciting roles in the industry today.
**Job Requirements**
+ Lead the development and deployment of AI/ML systems for Data protection with techniques from the realm of classical Machine learning, Generative AI and AI agents.
+ Develop scalable data pipelines for various AI/ML-driven solutions from building curated data pipelines, setting up automated evals, adopting latest and greatest inferencing platforms for rapid iterations.
+ Collaborate with data scientists and engineers to integrate AI into the broader products at NetApp. Effectively communicate complex technical artifacts to both technical and non-technical audiences.
+ Work with a great deal of autonomy and proactively bring open-source AI innovations into our research and experimentation roadmap. Ensure scalability, reliability, and performance of AI models in production environments.
+ Have a customer focus mindset and build AI/ML products that delight our customers.
+ Represent NetApp as an innovator in the machine learning community and promote the company's product capabilities in industry/academic conferences.
**Job Expectations**
+ The position is a Hybrid position, and the candidate is expected to work in NetApp Bangalore office at least two days a week.
**Required and Preferred Qualification**
+ Master's degree in computer science / applied mathematics / statistics / data science or equivalent experience.
+ 3+ years of experience in building MLOps pipelines, CI/CD pipelines, and ML systems lifecycle management.
+ Strong knowledge of optimizing and shipping machine learning and deep learning models to production.
+ Proficiency in Python, SQL and at least one cloud platform (AWS, Azure or GCP).
+ Excellent communication and collaboration skills, with demonstrated ability to work effectively with cross-functional teams and stakeholders of an organization
**Preferred Qualification**
+ 1+ years of experience in data engineering, including building and optimizing data pipelines and architectures.
+ Solid understanding of data science fundamentals and model evaluations, including supervised and unsupervised machine learning algorithms (both machine learning and deep learning).
+ Good understanding of cyber-security and data protection frameworks.
+ Experience of representing your work or company at AI/ML conferences.
+ Active GitHub profile showcasing relevant open-source AI/ML projects or Kaggle achievements.

At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.
**Equal Opportunity Employer:**
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, and any protected classification.
**Why NetApp?**
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
We enable a healthy work-life balance. Our volunteer time off program is best in class, offering employees 40 hours of paid time off each year to volunteer with their favourite organizations. We provide comprehensive benefits, including health care, life and accident plans, emotional support resources for you and your family, legal services, and financial savings programs to help you plan for your future. We support professional and personal growth through educational assistance and provide access to various discounts and perks to enhance your overall quality of life.
If you want to help us build knowledge and solve big problems, let's talk.

LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world's workforce in ways no other company can. We're much more than a digital resume -- we transform lives through innovative products and technology.
Every day, millions of posts, videos, and articles course through the LinkedIn feed, generating tens of thousands of comments every hour - and tens of millions more shares and likes.
Join the LSS-AI team and help create meaningful impact by connecting sellers and buyers to mutual growth opportunities! LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion dollar verticals at LinkedIn, and the LSS-AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform. This platform enables tens of millions of companies to connect with their future customers, driving significant economic value. As a member of the LSS-AI team, you will work on cutting-edge projects, including building Agentic and GenAI-powered search and recommendation systems, tuning and applying domain-specific LLMs, and collaborating with our partner vendors like OpenAI. You will have the opportunity to work with passionate AI engineers, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. Together, we are creating immense economic value for our customers using the largest global professional economic graph.
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
As part of a new and fast growing team of top-notch scientists and engineers, you will experience all the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise.
Responsibilities:
+ As a Manager, you will participate in key technical and design discussions with technical leads in the team.
+ You will lead the AI strategy for an area and work with the engineering and product leads to align it with the larger vision for the LinkedIn Sales ecosystem.
+ You will collaborate with application engineering, product, and partner teams to design machine learning solutions to power LSS products.
+ You will attract world class talent and provide technical guidance, career development, and mentoring to team members.
+ You will hold the team to a high quality bar for machine learning tech and actively reduce tech debt, designing systems that scale with algorithms and with time, and improve engineering productivity.
+ You will partner with data science & analytics teams, product & infrastructure teams to build and onboard new modeling use cases online.
Basic Qualifications:
+ MS/PhD degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related discipline.
+ 8+ years of experience in machine learning, artificial intelligence, or related fields.
+ 5+ years in an architect or technical leadership role driving large-scale AI initiatives.
+ Hands-on experience with end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and optimization.
+ Experience of leading a team of engineers as a people manager.
+ 1+ year(s) of management experience or 1+ year(s) of staff level experience with management training
Preferred Qualifications:
+ 3+ years of management experience.
+ MS or PhD in Computer Science, Statistics or related technical discipline
+ Experience with machine learning, optimization algorithms, and/or deep-learning techniques
+ Experience developing large scale systems
+ Leadership or mentorship experience is preferred
+ Analytical approach coupled with solid communication skills and a sense of ownership
+ Track record of producing papers in conferences such as KDD, . and Patenting Innovations
You will Benefit from our Culture:
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels
Suggested Skills
People Management
Clustered computing systems experience
Experience in building ML data systems
**India Disability Policy**
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit Data Privacy Notice for Job Candidates **
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants:

**Join Amgen's Mission of Serving Patients**
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Machine Learning Engineer
**What you will do**
Let's do this. Let's change the world. In this vital role as a Machine Learning Engineer, you will contribute to the development and maintenance of our GEN AI web applications across various Process Development functions(Drug Substance, Drug Product, Attribute Sciences & Combination Products) in Operations. This role is ideal for recent graduates or early-career professionals looking to gain hands-on experience in software development.
**Roles & Responsibilities:**
+ Implement, and optimize LLM-powered models for document processing, data extraction, and application Insights
+ Develop and optimize retrieval-augmented generation (RAG) pipelines to improve query processing and information retrieval
+ Work with large-scale structured and unstructured data to ensure efficient indexing, retrieval, and contextual relevance
+ Collaborate with the design and product teams to understand user needs and translate them into technical requirements.
+ Write clean, efficient, and well-tested code.
+ Participate in code reviews and provide constructive feedback.
+ Maintain system uptime and optimal performance
+ Learn and adapt to new technologies and industry trends like Prompt Engineering, AI tools and Retrieval-augmented generation (RAG) frameworks
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients. The (vital attribute) professional we seek is a (type of person) with these qualifications.
**Basic Qualifications:**
Master's degree / Bachelor's degree and 5 to 9 years
**Preferred Qualifications:**
**Functional Skills:**
+ Proficiency in Python and data manipulation libraries (Pandas, NumPy, etc.)
+ Familiarity with machine learning workflows and common ML libraries (scikit-learn, PyTorch, TensorFlow)
+ Working knowledge of cloud environments (AWS, Azure, or Google Cloud Platform)
+ Experience with popular large language models like OPEN AI
+ Experience with language models and frameworks like Langchain or llamaIndex
+ Proficiency with prompt engineering, model fine tuning
+ Familiarity with DevOps CICD build and deployment pipeline
+ Experience with design patterns, data structures, test-driven development.
**Professional Certifications:**
+ AWS, Data Science Certifications(preferred)
**Soft Skills:**
+ Excellent analytical and troubleshooting skills.
+ Strong verbal and written communication skills.
+ Ability to work effectively with global, virtual teams.
+ High degree of initiative and self-motivation.
+ Ability to manage multiple priorities successfully.
+ Team-oriented, with a focus on achieving team goals.
+ Strong presentation and public speaking skills.
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

**Join Amgen's Mission of Serving Patients**
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
**Machine Learning Engineer**
**What you will do**
Let's do this. Let's change the world. In this vital role We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.
**Roles & Responsibilities:**
+ Collaborate with data scientists to develop, train, and evaluate machine learning models.
+ Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
+ Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
+ Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency.
+ Develop and implement monitoring systems to track model performance and identify issues.
+ Conduct A/B testing and experimentation to optimize model performance.
+ Work closely with data scientists, engineers, and product teams to deliver ML solutions.
+ Stay updated with the latest trends and advancements
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients.
**Basic Qualifications:**
+ Master's degree / Bachelor's degree and 5 to 9 years (Job Code's Discipline and/or Sub-Discipline)
**Functional Skills:**
**Must-Have Skills:**
+ Solid foundation in machine learning algorithms and techniques
+ Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
+ Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
+ Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and interpersonal skills
**Good-to-Have Skills:**
+ Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
+ Experience with data engineering and pipeline development
+ Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
+ Knowledge of NLP techniques for text analysis and sentiment analysis
+ Experience in analyzing time-series data for forecasting and trend analysis
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Responsibilities:

Machine Learning Development & Implementation (40%)

• Design and implement end-to-end ML pipelines for recommendation systems, search ranking, and classification problems
• Build and optimize traditional ML models using techniques such as ensemble methods, SVMs, gradient boosting, and neural networks
• Develop time series forecasting models and ranking algorithms for complex business applications
• Implement feature engineering pipelines that handle real-world data noise and edge cases
• Create robust data preprocessing and validation systems that ensure model reliability in production

Production ML Systems & Deployment (25%)

• Deploy ML models using Docker containerization and REST API frameworks (Flask/FastAPl)
• Implement model serving solutions on Azure Container Instances with proper monitoring and

alerting

• Build MLOps pipelines using MLflow for experiment tracking and model registry management
• Design scalable data workflows using Apache Airflow and Azure Data Factory for ETL operations
• Establish model versioning, rollback strategies, and performance monitoring in production environments

Technical Leadership & Collaboration (20%)

• Serve as a technical sounding board for AI team members on ML architecture and approach decisions
• Mentor team members on best practices for production ML system design and implementation
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders
• Collaborate across AI, web development, and system architecture teams toensure seamless integration
• Guide strategic decisions on when to use traditional ML versus generative AI approaches

Strategic ML Decision Making (15%)

• Evaluate problems to determine optimal solutions: classical ML, GenAI, or simpler analytical methods
• Integrate generative AI tools effectively into workflows without over-relying on them
• Design ML systems that integrate seamlessly with existing web application architectures
• Provide technical guidance onmodel selection, evaluation metrics, and performance optimization
• Stay current with ML best practices while maintaining focus on practical, business-driven solutions

Required Qualifications

Education & Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field
• 4+ years of hands-on experience building and deploying machine learning systems in production
• Proven experience working in non-technical business domains (healthcare, finance, retail, HR, etc.)
• Track record of mentoring technical team members and leading collaborative projects

Core Technical Skills

• Programming Excellence: Expert-level Python proficiency with focus on clean, maintainable, production-ready code
• Traditional ML Expertise: Deep understanding of classification, regression, ranking, and recommendation algorithms
• Production ML: Experience with MLOps practices, model deployment, monitoring, and lifecycle management
• Data Engineering: Proficiency with data pipeline development, ETL processes, and handling messy real-world datasets
• Cloud Platforms: Hands-on experience with Azure ML Studio, Azure Container Instances, and Azure Data Factory

Specialized Experience:

• Experience building recommendation engines, search ranking systems, or time series forecasting models
• Background in A/B testing methodologies and measuring business impact of ML initiatives
• Knowledge of feature stores, model registry systems, and ML experiment tracking
• Understanding of model interpretability, bias detection, and fairness in ML systems
• Experience with both structured and unstructured data processing at scale
• Experience with deep learning frameworks (TensorFlow, PyTorch) for appropriate use cases

Preferred Qualifications

• Knowledge of natural language processing techniques and text classification systems
• Background in building ML systems for talent acquisition, recruiting, or HR technology
• Experience with real-time ML inference and low-latency model serving
• Understanding of distributed computing and large-scale data processing