Develop model evaluation frameworks covering reasoning, instruction following, hallucination detection, tool calling, safety, robustness, and structured output quality.
Evaluate and optimize retrieval-augmented generation systems through retrieval analysis, embedding model comparison, reranking, chunking strategies, and groundedness assessment.
Design and execute agent and tool-calling benchmarks that measure task completion, tool selection accuracy, failure recovery, and operational safety.
Optimize model serving performance through quantization, batching strategies, cache management, inference tuning, and serving-stack evaluation.
Implement experiment tracking, model governance, lineage management, release gating, and deployment workflows using enterprise MLOps practices.
Establish production monitoring, quality drift detection, observability metrics, security testing, and rollback criteria for deployed AI solutions.
Required Knowledge and Experience
3+ years of IT experience with a Bachelor's Degree in Engineering, MCA, or MSc. with 3+ years of software engineering or machine learning experience, including 2+ years of hands-on Generative AI or Large Language Model development.
Experience with Python, PyTorch, Hugging Face Transformers, Datasets, PEFT, and model fine-tuning workflows.
Experience implementing Large Language Model evaluation, retrieval-augmented generation, model benchmarking, and experiment tracking frameworks.
Experience with Linux, Docker, Kubernetes, Git, REST APIs, and cloud or GPU-based model deployment environments.
Experience with MLflow or Weights & Biases for experiment tracking, model lifecycle management, and artifact versioning.
Preferred Skills & Competencies
Experience with direct preference optimization (DPO), TRL, DeepSpeed, Fully Sharded Data Parallel (FSDP), or distributed training techniques.
Experience deploying and optimizing models using vLLM, NVIDIA TensorRT-LLM, SGLang, or comparable inference-serving platforms.
Experience with RAGAS, DeepEval, TruLens, or similar evaluation and observability frameworks.
Experience in AI Ops, IT service management, incident management, observability platforms, knowledge systems, or automated remediation workflows.
Experience implementing OpenTelemetry, Prometheus, Grafana, model monitoring, security testing, and production release governance.
Physical Job Requirements
The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position.
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Benefits & Compensation
Medtronic offers a competitive Salary and flexible Benefits Package
A commitment to our employees lives at the core of our values. We recognize their contributions. They share in the success they help to create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every career and life stage.
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- This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP).
