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Senior MLOps Engineer

Industry: Hospitals & Physicians Clinics
Remote
Company size: 251-10K
Full-time/Part-time

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Job description

A well-established company that is determined to become the most consumer-centric health organization by leveraging cutting-edge technologies and innovations, is looking for a Senior MLOps Engineer. The engineer will play an instrumental role in deploying robust, scalable machine learning solutions. The candidate will ensure these are tailored to meet the expansive needs of varied healthcare services. The company is driving a transformation in health care by expanding their footprint and providing more accessible, supportive, and personalized care.  This role demands a high level of proficiency in machine learning technologies and programming, coupled with rigorous vetting processes to maintain the highest standards of data integrity and security.

 

Job Responsibilities:


  • Rapidly develop and deploy production-ready ML models, with a focus on scalability and monitoring across a broad range of applications within healthcare
  • Write efficient, maintainable, and scalable Python code tailored to specific business needs
  • Build high-performance, multi-tenant deployment architectures, and sophisticated model monitoring systems
  • Directly engage with internal stakeholders to incorporate feedback and refine the ML-driven products through quick iteration cycles
  • Uphold stringent security protocols and processes in the deployment and maintenance of machine learning models
  • Drive the continuous advancement of MLOps practices within the healthcare industry by developing innovative solutions and advocating for best practices


Job Requirements:


  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 5+ years of relevant experience as an MLOps Engineer
  • At least 3+ years of experience with transformer-based models and NLP, preferably in a healthcare context
  • Strong track record of fine-tuning, running large-scale training jobs, and managing model servers like vLLM, TGI, or TorchServe
  • Proficiency in data science tools such as Pandas, Notebooks, Numpy, and Scipy
  • Demonstrable experience with both relational and non-relational databases
  • Extensive experience with TensorFlow or PyTorch, and familiarity with HuggingFace
  • Knowledge of model analysis and experimentation frameworks such as MLFlow, W&B, and tfma is preferred
  • Comfortable with a Linux environment and stringent data security practices
  • Must pass a rigorous vetting process, including extensive background checks to ensure the highest standards of data security and integrity
  • Fluent in English communication, both written and spoken

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