Manager of Machine Learning

Location: Grand Rapids, MI - Remote (any location)

Ava Sure is revolutionizing healthcare with cutting-edge virtual care solutions that protect patients and empower clinical teams. We’re proud of our collaborative culture where innovation thrives and every team member is valued.
Apply today and help us shape the future of healthcare!

The Machine Learning Manager is a hands-on technical leader and people manager responsible for designing, building, deploying, and scaling production-grade machine learning systems, with a strong emphasis on computer vision, deep learning, and large language models (LLMs). This role leads a team of machine learning engineers while remaining actively involved in architecture decisions, model development, ML Ops, and critical code paths.

The Machine Learning Manager partners closely with Product, Engineering, Clinical, and Operations teams to deliver reliable, ethical, and scalable AI solutions that directly impact customer outcomes. The ideal candidate combines strong technical depth, pragmatic leadership, and a bias toward execution, and thrives in environments where strategy and hands-on delivery are equally important.

• Lead the end-to-end machine learning lifecycle, including data ingestion, model development, training, evaluation, deployment, monitoring, and iteration.
• Own and evolve ML Ops architecture, including CI/CD for models, feature pipelines, model versioning, monitoring, and retraining strategies.
• Serve as a player-coach, contributing directly to design reviews, code reviews, prototyping, and implementation for high-impact initiatives.
• Architect and deploy computer vision models (e.g., CNNs, transformers, multimodal models) and LLM-based systems (e.g., prompt pipelines, fine-tuning, RAG, evaluation frameworks).
• Establish and track model performance, reliability, scalability, and ethical AI metrics, ensuring compliance with internal standards and regulatory expectations.
• Lead project planning, feasibility analysis, and technical scoping for new AI-driven functionality.
• Identify technical risks early and develop mitigation and contingency plans.
• Ensure strong testing discipline, including unit testing, integration testing, and test-driven development (TDD) practices.
• Apply and mentor on software design patterns, debugging strategies, and production troubleshooting best practices.
• Collaborate cross-functionally to align priorities, manage dependencies, and communicate progress, tradeoffs, and outcomes.
• Write and present technical and executive-level status updates to stakeholders.
• Oversee software and model releases and communicate release readiness and impact
• Artificial Intelligence (AI)
• Computer Vision
• Data Modeling & Data Science
• Predictive Analytics
• ML Ops & Dev Ops
• Strategic Planning & Execution
• Technical Project Management
• Ethical AI & Model Governance

• Directly manage machine learning engineers, including task assignment, performance management, mentoring, and career development.
• Conduct regular 1:1 meetings, support goal setting, and provide actionable feedback.
• Identify and remove blockers to keep the team productive and focused.
• Participate in hiring decisions, technical interviews, and onboarding of new team members.
• Partner with senior leadership and HR on team growth planning, compensation, and performance calibration.
• Foster a culture of psychological safety, transparency, accountability, and continuous learning

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’s preferred).
• 7+ years of professional experience in machine learning or related engineering roles.
• 1–3+ years of people leadership experience, preferably managing ML or data-focused teams.
• Demonstrated, hands-on experience with:
  • Computer vision frameworks (e.g., PyTorch, Tensor Flow, OpenCV).
  • LLMs and modern NLP systems, including prompt engineering, fine-tuning, evaluation, and deployment.
• At least two machine learning frameworks.
• Strong proficiency in Python; experience with production-grade ML systems.
• Proven ability to define, estimate, and deliver complex technical projects on…