Medtronic is looking to solve complex business problems by designing, developing, and implementing machine learning models and algorithms. The company aims to improve healthcare access and equity, drive innovation, and enhance patient care within its Diabetes business, which is undergoing a separation to promote future growth.
Requirements
- 5+ years of industry experience in writing production level, scalable code (e.g. in Python)
- 4+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning
- 4+ years of industry experience with distributed computing frameworks such as PySpark
- 4+ 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.).
- 4+ years of industry experience with major cloud computing services like AWS or Azure or GCP
- 1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, Langgraph, PGVector, Pinecone, Bedrock.
- Proficient in containerization services
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 4 years of relevant experience OR Master's degree with a minimum of 2 years relevant experience OR PhD with 0 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.
