Medtronic is looking to solve complex business problems by designing, developing, and implementing machine learning models and algorithms.
Requirements
- 7+ years of industry experience in writing production level, scalable code (e.g. in Python)
- 5+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning
- 5+ years of industry experience with distributed computing frameworks such as PySpark
- 5+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and other libraries (like scikit-learn, spacy, genism etc.).
- 5+ years of industry experience with major cloud computing services like AWS or Azure or GCP
- 2+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like LangChain, LangGraph, PGVector, Pinecone, Bedrock.
- Experience in building Agentic AI applications.
Responsibilities
- Design, develop, and implement machine learning models and algorithms to solve complex business problems.
- Use software design principles to develop production ready code.
- Collect, preprocess, and analyze large datasets to train and evaluate machine learning models.
- Optimize and fine-tune machine learning models for performance and accuracy.
- Deploy machine learning models into production environments and monitor their performance.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Stay up to date with the latest advancements in machine learning and apply them to improve existing models and algorithms.
Other
- Requires a Bachelor's degree and minimum of 7 years of relevant experience OR Master's degree with a minimum of 5 years relevant experience OR PhD with 3 years relevant experience.
- Collaborate with data scientists and stakeholders to understand business requirements and translate them into machine learning solutions.
- Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
- Document and communicate machine learning solutions, methodologies, and results to technical and non-technical stakeholders.
- Mentor and provide guidance to junior Machine Learning Engineers.
