Senior Manager of Machine Learning, Applied AI

SimplePractice

1d•$233,000 - $285,000

About The Position

We’re seeking a Senior Manager, Applied AI to build and lead a high-performing team of senior Machine Learning Engineers focused on empowering clinicians with intelligent, reliable, and scalable AI-driven product features. In this role, you’ll build and guide a team of experienced ICs who are building next-generation tools that enhance clinician workflows, elevate care quality, and drive operational efficiency through machine learning. From experimentation and prototyping to scalable deployment, your team touches every part of the ML lifecycle. As a manager, your leadership will be critical to scaling our impact, aligning technical execution with strategic product priorities, and fostering a culture of innovation, accountability, and technical excellence.

Requirements

8+ years of experience in machine learning, with at least 3+ years managing high-performing technical teams
Proven track record of bringing ML prototypes into production in a fast-paced, product-focused environment
Deep understanding of LLM workflows, including prompt engineering, evaluation, and deployment
Strong engineering skills, with comfort working across the ML/infra stack (Python, cloud, orchestration tools)
Strong research skills, with high bar for
Ability to inspire, coach, and develop senior engineers while setting a high technical bar
Strong cross-functional communication skills; capable of translating AI complexity into business value
Proactive, solution-oriented mindset with a bias toward clarity, impact, and continuous learning
Proficiency with Python, cloud services (AWS preferred), and ML pipeline orchestration (Outerbounds, Argo, etc.)
Familiarity with LLM eval frameworks, prompt management tools (e.g., Langfuse), and vector stores
Experience leading teams focused on LLMs, RAG, or other advanced ML architectures
Hands-on experience with ML observability, CI/CD, Kubernetes, or similar technologies

Nice To Haves

Background in clinical or operational healthcare workflows

Responsibilities

Lead, mentor, and grow a team of senior-level ML engineers working on applied AI in production environments
Partner with ML Platform team to drive technical roadmap development and execution in alignment with product and business goals
Ensure high-quality and timely delivery of advanced data analysis, prototypes, evaluations, and productionized ML workflows
Provide hands-on guidance on LLM workflows, evaluation strategies, and model lifecycle best practices
Collaborate closely with Product, Design, Engineering, and ML Platform to define scope, success metrics, and project plans
Translate complex technical opportunities and risks into clear, actionable plans for cross-functional stakeholders
Act as a key advisor on AI capabilities, helping to shape our roadmap for AI-enabled clinician tools
Champion a strong experimentation culture grounded in domain understanding, user needs, and rigorous evaluation
Encourage novel applications of LLMs, retrieval-augmented generation (RAG), and other emerging techniques to drive value
Advocate for scalable, reliable, and safe deployment of ML solutions in real-world clinical contexts
Own team planning, capacity management, and execution tracking using modern tools
Collaborate with ML platform, DevOps, and data engineering partners to ensure reliable infrastructure and monitoring
Drive adoption of best practices in model versioning, prompt tuning, performance tracking, and incident response