Senior MLOps Engineer

1 month ago

New York, United States Harnham Full time
Senior MLOps Engineer

Fully Remote

6-Month Contract to Hire

$60-$80/hr

Are you looking to advance your MLOps career in an innovative and AI driven healthcare company? Apply below

THE COMPANY

We are currently partnered with one of the largest healthcare systems in the U.S. - they are disrupting the healthcare field by innovating and advancing ML/AI through their systems to directly impact patients and hospitals.

THE ROLE
  • Responsible for design and development of production grade Machine Learning solutions. Help set ML engineering standards (development stack, sample starter projects, etc.)
  • Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in ML platform and development ecosystem
  • Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies
  • Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions
  • Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency
  • Evaluate and optimize model prototypes for real-world performance
YOUR SKILLS AND EXPERIENCE

A successful MLOps Engineer within this role will likely have the following skills and experience:
  • Bachelor's degree in Business Administration, Computer Science, Data Systems or Data Engineering preferred
  • 5+ years of experience in Lead Software Engineering position with at least 3-years hands on with implementing AI/ML solutions.
  • Expert in Python, including some experience with machine learning libraries and frameworks such as sklearn, TensorFlow, PyTorch, or Keras
  • Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring.
  • Expertise in Relational Databases, MySQL, In-Memory databases, NoSQL databases, AWS is a significant plus. Understanding of containerization (Docker & Linux experience).
  • Understanding of GPU acceleration techniques


HOW TO APPLY

Please register your interest by sending your resume via the Apply link on this page.

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