The Role

AI & ML is at the foundation of what we do. We are looking to fundamentally change the way pediatric healthcare is delivered. Our ML researchers collaborate closely with internal SMEs and the product team to develop leading computer vision and generative multi-modal models that solve real problems. We are seeking an experienced and passionate MLOps Engineer to join this team and play a crucial role in bringing these complex ML/AI models from prototype to production. This role will additionally be working with our engineering teams to ensure we not only provide a framework for the ML team but can also effectively productize and utilize the models.

Responsibilities

• Take prototypes developed by the ML modeling team and drive them into production, ensuring smooth deployment and management of ML models on cloud at scale.
• Work in a highly collaborative and diverse team environment, actively contributing to team goals, participating in fast iteration cycles, and adapting to evolving project requirements.
• Collaborate with ML scientists, software engineers, data engineers and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated model deployment.
• Collaborate with DevOps & infrastructure engineers to effectively manage cloud compute resources for ML model deployment, monitoring, and performance optimization.
• Monitor real-time performance of deployed models, analyze performance data, and proactively identify and address performance issues to ensure optimal model performance.
• Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability in a timely and efficient manner.
• Contribute to the continuous improvement of the team’s processes and workflows, and share knowledge and expertise with team members to promote a collaborative learning environment.

Qualifications

• Minimum 3 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments.
• Minimum 5 years of experience in backend/ML/data development with a strong understanding of server-side programming languages (Python, Java, etc.).
• Strong experience with tools and technologies such as Git, Docker, Kubernetes, Jenkins, CI/CD pipelines, monitoring and logging frameworks, and cloud platforms (e.g., AWS, GCP, Azure).
• Proven track record of deploying models on services such as Google’s Vertex AI ML platform, Amazon SageMaker or Azure ML.
• Hands-on experience working with both generative and computer vision models.
• Strong communication skills, with the ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Excellent teamwork and collaboration skills, with the ability to work effectively in cross-functional teams, adapt to fast iteration cycles, and contribute to team goals.
• Proven ability to work in a fast-paced, dynamic, and innovative environment, with a strong sense of ownership and accountability for delivering high-quality results.
• Experience working in a geographically distributed team environment
• Plus: Expert knowledge in architecting and scaling distributed processing systems (like Spark or Dask) for high performance computing to support model training and inference.

Why Frontera Health?

• Opportunity to be at the forefront of innovation in pediatric healthcare.
• Work on challenging and impactful projects that leverage cutting-edge technologies.
• Collaborate with a talented and passionate team in a fast-paced and dynamic environment.
• Make a real difference in the lives of children and families in rural communities.
• Competitive salary and benefits package.

Join us in building the future of behavioral healthcare!