Primary Responsibilities:

- Lead the design, development, and implementation of scalable AI/ML solutions, leveraging Python, SQL, pandas, numpy, and modern ML frameworks (TensorFlow, PyTorch, Scikit Learn)
- Oversee end to end ML workflowsfrom data preparation, feature engineering, EDA, and model development to evaluation, deployment, and continuous monitoring
- Guide model selection, optimization, and tuning, ensuring solutions balance performance, explainability, cost, and Responsible AI principles
- Build and maintain production grade ML pipelines with orchestration and experiment tracking tools such as MLflow, Feature Stores, ONNX, and vector databases
- Lead drift analysis, observability, and model health monitoring to ensure ongoing accuracy, reliability, and robustness in production environments
- Design and support scalable, multi cloud ML infrastructure (Azure/GCP primary, AWS optional), incorporating best practices for compute, storage, networking, and distributed data processing
- Collaborate with data engineering teams to integrate real time and batch pipelines built on Synapse/Big Query, Dataflow/Databricks, and Kafka/EventHub/Pub Sub
- Work closely with engineering, product, data science, and UX to translate business requirements into actionable technical solutions and architecture patterns
- Review and guide the creation of architecture diagrams, C4 models, ADRs, and technical specifications as part of engineering governance
- Mentor and coach data scientists and ML engineers on best practices in model development, experimentation, coding standards, optimization, and cloud native ML deployment




- Ensure ML systems meet high standards of scalability, security, reliability, automation, observability, and operational excellence
- Collaborate with front end teams where needed to ensure ML components integrate seamlessly with product workflows and user-facing experiences
- Stay current with emerging AI/ML tools, frameworks, and research; evaluate applicability to current and future projects
- Communicate technical concepts, design trade-offs, and recommendations clearly to both technical and non technical stakeholders, including leadership
- Document methodologies, experiments, findings, and implementation details to ensure maintainability and knowledge sharing across teams
- Comply with company policies, employment terms, and organizational directives related to work arrangements and project assignments

Required Qualifications:

- 6+ years of experience in Data Science, AI/ML, or a similar role
- Experience with the full life cycle of AI/ML projects, including EDA, model development, tuning, and drift analysis
- Hands-on experience in delivering production-grade AI/ML projects
- Solid programming skills in Python, with experience in pandas, numpy, and SQL
- Solid understanding of mathematical and statistical concepts
- Proficiency in frameworks such as Scikit Learn, TensorFlow, and PyTorch

- Proven excellent problem-solving and analytical thinking skills
- Proven solid communication and collaboration skills to work effectively in a team workplace

Preferred Qualifications:

- Familiarity with the US Healthcare domain
- Knowledge of Big Data technologies (PySpark, Hadoop) and data streaming tools (Kafka, etc.)

📌 Ai Ml Engineer (Noida)
🏢 Optum
📍 Noida