Jobs · Engineering

ML Engineer

Ladders · United States · 3 wk ago
RemoteRemoteEngineering$110k–$130k/yrFull-time
For our client, we are seeking a ML Engineer to join the team of a leader in the Healthcare space. This role will focus on building and operationalizing machine learning capabilities that support healthcare applications and data-driven decision-making. You will work closely with backend teams and other technical partners to deploy reliable models, improve data pipelines, and strengthen the systems that bring ML into production. The position blends software engineering, MLOps, and data engineering to help ensure models are scalable, monitored, and maintainable in a healthcare environment. Location: Remote - US based candidates only, no visa sponsorship available Compensation: $110,000 – $130,000 annually Responsibilities Build and maintain CI/CD pipelines for machine learning, emphasizing automated testing and model deployment Deploy ML models as scalable APIs and microservices, ensuring they fulfill performance requirements Implement monitoring tools to track model performance, data drift, and system health Develop and optimize ETL processes to transform healthcare data into usable datasets Help maintain feature stores and data layers to ensure consistency across environments Collaborate with backend teams to integrate ML outputs into healthcare applications Write clean, maintainable code and participate in code reviews to enhance system reliability Qualifications Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field 3-5 years of professional experience in software or data engineering, with 2+ years in machine learning production environments Strong proficiency in Python and familiarity with SQL; knowledge of compiled languages such as Go or Java is a plus Hands-on experience with major cloud providers (AWS, Azure, GCP) and containerization (Docker) Familiarity with ML libraries (PyTorch, Scikit-learn) and MLOps tools such as Airflow or Prefect Experience with data processing frameworks such as Pandas and Spark Benefits Programs to support physical and financial well-being Onboarding experience includes meeting with managers and peers Travel arrangements for on-site onboarding are paid by the company Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.

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