MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- Senior ML Engineer leading the strategic direction of machine learning infrastructure for global food delivery platform. Collaborating with Data Science team for seamless model deployment and innovation.
Responsibilities
- Take a leadership role in shaping the strategic direction of machine learning infrastructure
- Identify opportunities for innovation and improvement
- Drive the development of cutting-edge solutions for performance, scalability, and reliability of ML systems
- Collaborate with Data Science team to ensure seamless deployment of models
- Architect and oversee development of complex machine learning pipelines
- Manage both real-time and batch inference systems
- Mentor and guide mid-level Machine Learning Engineers
- Conduct comprehensive code reviews and identify areas for improvement
- Communicate effectively with both technical and non-technical stakeholders
- Lead integration of new technologies into the infrastructure
Requirements
- Expert-level proficiency with cloud technologies (ideally AWS)
- Extensive experience with containerization and orchestration (preferably Kubernetes)
- Deep understanding of software development, DevOps, and MLOps best practices
- Extensive experience in designing, deploying, and maintaining scalable models and services in production environments
- Strong understanding of Machine Learning
- Experience with MLflow for experiment tracking and model management
- Experience with Airflow or Dagster for orchestrating end-to-end ML pipelines
- Significant experience with Data Engineering, Kafka, and stream processing
- Proficiency in Python and SQL; or any other programming languages is a strong plus.
Benefits
- Inclusion, Diversity & Belonging
- Fun, fast-paced and supportive culture
- Professional development opportunities
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