AI / ML Engineer @ Optum

Location: Gurgaon, Noida, Bangalore, Chennai

Primary Responsibilities:

• WHAT
• Business Knowledge:
• Capable of understanding the requirements for the entire project (not just own features)
• Capable of working closely with PMG during the design phase to drill down into detailed nuances of the requirements
• Has the ability and confidence to question the motivation behind certain requirements and work with PMG to refine them
• Design:
• Can design and implement machine learning models and algorithms
• Can articulate and evaluate pros/cons of different AI/ML approaches
• Can generate cost estimates for model training and deployment
• Coding/Testing:
• Builds and optimizes machine learning pipelines
• Knows & brings in external ML frameworks and libraries
• Consistently avoids common pitfalls in model development and deployment
• HOW
• Quality:
• Solves cross-functional problems using data-driven approaches
• Identifies impacts/side effects of models outside of immediate scope of work
• Identifies cross-module issues related to data integration and model performance
• Identifies problems predictively using data analysis
• Productivity:
• Capable of working on multiple AI/ML projects simultaneously and context switching between them
• Process:
• Enforces process standards for model development and deployment
• Independence:
• Acts independently to determine methods and procedures on new or special assignments
• Prioritizes large tasks and projects effectively
• Agility:
• Release Planning: Works with the PO to do high-level release commitment and estimation
• Works with PO on defining stories of appropriate size for model development
• Agile Maturity: Able to drive the team to achieve a high level of accomplishment on the committed stories for each iteration
• Shows Agile leadership qualities and leads by example
• WITH
• Team Work:
• Capable of working with development teams and identifying the right division of technical responsibility based on skill sets
• Capable of working with external teams (e.g., Support, PO, etc.) that have significantly different technical skill sets and managing the discussions based on their needs
• Initiative:
• Capable of creating innovative AI/ML solutions that may include changes to requirements to create a better solution
• Capable of thinking outside-the-box to view the system as it should be rather than only how it is
• Proactively generates a continual stream of ideas and pushes to review and advance ideas if they make sense
• Takes initiative to learn how AI/ML technology is evolving outside the organization
• Takes initiative to learn how the system can be improved for the customers
• Should make problems open new doors for innovations
• Communication:
• Communicates complex AI/ML concepts internally with ease
• Accountability:
• Well versed in all areas of the AI/ML stack (data preprocessing, model training, evaluation, deployment, etc.) and aware of all components in play
• Leadership:
• Disagree without being disagreeable
• Use conflict as a way to drill deeper and arrive at better decisions
• Frequent mentorship
• Builds ad-hoc cross-department teams for specific projects or problems
• Can achieve broad scope 'buy in' across project teams and across departments
• Takes calculated risks
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• B.E/B.Tech/MCA/MSc/MTech
• 5+ years of experience working on multiple layers of technology
• Experience deploying and maintaining ML models in production
• Experience in Agile teams
• Working experience or good knowledge of cloud platforms (e.g., Azure, AWS, OCI)
• Experience with one or more data-oriented workflow orchestration frameworks (Airflow, KubeFlow etc.)
• Familiarity with traditional software monitoring, scaling, and quality management (QMS)
• Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.)
• Knowledge of model versioning and deployment using tools like MLflow, DVC, or similar platforms
• Hands-on knowledge of OpenSource adoption and use cases
• Good understanding of Data/Information security
• Proficient in Data Structures, ML Algorithms, and ML lifecycle
• Product/Project/Program Related Tech Stack:
• Machine Learning Frameworks: Scikit-learn, TensorFlow, PyTorch
• Programming Languages: Python, R, Java
• Data Processing: Pandas, NumPy, Spark
• Visualization: Matplotlib, Seaborn, Plotly
• Familiarity with model versioning tools (MLFlow, etc.)
• Cloud Services: Azure ML, AWS SageMaker, Google Cloud AI
• Design, implement, and maintain CI/CD pipelines for MLOps and DevOps function
• Good knowledge in Engineering Practices
• Demonstrated excellent problem-solving skills
• Demonstrated excellent verbal, written, and interpersonal communication skills