Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact.
A Day in the LifeAs an IT Developer focused on Applied AI and Large Language Model engineering, you will design, evaluate, optimize, and operationalize enterprise AI systems across the complete model lifecycle. You will partner with platform engineers, data engineers, security teams, and domain experts to improve model quality, deploy production-ready AI solutions, establish evaluation frameworks, and drive measurable outcomes through data-driven experimentation and governance.Responsibilities may include the following and other duties may be assigned.
- Design and implement training, fine-tuning, and adaptation pipelines for open-weight Large Language Models using supervised fine-tuning, LoRA, QLoRA, and Parameter-Efficient Fine-Tuning (PEFT) techniques.
- Build and curate high-quality datasets from operational data sources, incidents, runbooks, logs, knowledge articles, and validated interactions for model training and evaluation.
- 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.
Recruitment Fraud Alert
We are aware of phishing scams targeting job seekers. Please keep the following in mind:
Apply only through official Medtronic channels. All legitimate Medtronic recruiting communications come from approved Medtronic platforms and official @medtronic.com email addresses.
Medtronic will never ask for payment or sensitive personal information (such as bank account or Social Security details) during early stages of the hiring process. Any such requests are not legitimate.
If you receive a suspicious message claiming to be from Medtronic, do not respond, click links, or open attachments.
If you have any questions, concerns regarding the authenticity of a communication alleged to have been made by or on behalf of Medtronic, please contact us immediately at [email protected].
Benefits & CompensationMedtronic 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.
This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP).Skills Required
- Bachelor's degree in Engineering, MCA, or MSc.
- 3+ years of IT, software engineering, or machine learning experience.
- 2+ years of hands-on Generative AI or Large Language Model development experience.
- 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.
- Experience with DPO, TRL, DeepSpeed, 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 AIOps, 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.
Medtronic Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Medtronic and has not been reviewed or approved by Medtronic.
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Healthcare Strength — Health coverage is considered comprehensive, with high-quality medical, dental, and vision options through major providers and added mental-health resources. These programs are frequently highlighted as a core strength of the package.
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Parental & Family Support — Parental and family benefits stand out, including up to 24 weeks paid leave for U.S. birthing parents, 12 weeks for other parents, and a global Family Care Leave at 100% pay. Family-building support (fertility, adoption/surrogacy reimbursements) and backup care further reinforce this strength.
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Retirement Support — A 401(k) with company match is described as competitive and reliable for long-term savings. Additional financial programs, such as tuition assistance and charitable-gift matching, complement retirement planning.
Medtronic Insights
What We Do
Medtronic is a global healthcare solutions company operating in approximately 160 countries. We are committed to improving lives through our medical technologies, services, and solutions. Since our beginning, 60 years ago, our Mission has remained the same: to alleviate pain, restore health, and extend life for people around the world. The Mission is our ethical framework and inspirational goal guiding our day-to-day work. It reminds us that our efforts are transforming millions of lives each year. To meet the needs of patients and healthcare professionals around the globe, we operate from more than 370 locations in approximately 160 countries.









