Senior Machine Learning Engineer (Healthcare)

Scope of the role: In this role as a Senior Machine Learning Engineer, you will: • Design and implement data ingestion, model training, validation, deployment and monitoring pipelines across the organization • Optimize ML infrastructure and systems for maintainability, scalability, robustness, efficiency, and operating costs • Collaborate with product stakeholders, data scientists and engineering teams to design and implement AI / ML solutions for complex business problems and use cases • Define reference architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models • Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments Basic Qualifications: • Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience • 5+ years of experience designing large scale, complex, data intensive, AI / ML applications in an industrial setting • Substantial depth and breadth in system design, latency optimization, cloud infrastructure optimization, knowledge graphs, and MLOps • Deep understanding of CS fundamentals, computational complexity and algorithm design • Experience with building large-scale distributed systems in an agile environment and the ability to build quick prototypes • Excellent knowledge of Python and core data science libraries including Pandas, NumPy and other similar libraries • Experience mentoring junior team members • Excellent problem solving and communication skills Preferred Qualifications • Knowledge of the healthcare domain and experience with applying AI to healthcare data • Experience with AWS especially in relation to ML workflows with SageMaker, ECS, serverless compute and storage such as S3 and Snowflake