Machine Learning Ops Engineer

We are seeking a dedicated and innovative Machine Learning Ops Engineer to join our dynamic team. This role is essential for bridging the gap between machine learning, software engineering, and platform operations, contributing to impactful solutions in a collaborative environment. Responsibilities

• Design and implement automated ML pipelines for model training, evaluation, and deployment.
• Build and manage scalable model serving infrastructure for real-time and batch scoring.
• Architect and operate a sub-model orchestration layer compliant with regulatory requirements.
• Design and maintain a feature store architecture to ensure training-serving consistency.
• Implement and govern LLM API integrations, ensuring effective prompt management and cost tracking.
• Establish production monitoring and alerting systems for model performance and pipeline integrity.
• Automate infrastructure provisioning using Infrastructure-as-Code practices.
• Define and lead the enterprise MLOps platform strategy, mentoring junior engineers along the way.
• Establish CI/CD workflows to facilitate rapid and safe ML iteration.
• Engage in other duties and special projects as assigned.

• Bachelor’s or Master’s Degree in Computer Science, Software Engineering, or a related technical field.
• 7+ years of professional experience in DevOps, Data Engineering, or ML Engineering, with a focus on Machine Learning operations.
• Expertise in containerization and orchestration technologies such as Docker and Kubernetes.
• Proficiency in ML lifecycle tooling and cloud services, particularly AWS.
• Strong programming skills in Python, with experience in Bash scripting.

Preferred Skills

• Experience in healthcare or regulated data environments, with familiarity in HIPAA compliance.
• Knowledge of stream processing and event-driven pipeline design.
• Experience with LLM API integration and management.
• Strong interpersonal skills and ability to communicate technical concepts clearly.
• A proactive and curious mindset, eager to adopt emerging MLOps tools and practices.

We believe in fostering a diverse, equitable, and inclusive workplace where all team members feel valued and empowered to contribute their unique perspectives. We encourage applicants from all backgrounds to apply and join us in our mission to create innovative solutions.