Senior Manager, Applied AI

Summary

Join SimplePractice as a Senior Manager, Applied AI and lead a team of senior Machine Learning Engineers. You will build next-generation tools enhancing clinician workflows, elevate care quality, and drive operational efficiency through machine learning. Your team will be involved in the entire ML lifecycle, from experimentation to deployment. You will collaborate with various teams to define project scopes and success metrics. Champion a culture of experimentation and innovation, advocating for scalable and safe ML solutions. You will also manage team planning, capacity, and execution, ensuring reliable infrastructure and monitoring.

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

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

Preferred Qualifications

Background in clinical or operational healthcare workflows

Benefits

• Privatized Medical, Dental & Vision Coverage
• Work From Home stipend
• Flexible Time Off (FTO), wellbeing days, paid holidays, and Summer Fridays
• Monthly Meal Reimbursement
• Holiday Bonus, 15-day Aguinaldo
• Hybrid Work Schedule & Catered Lunch
• A relocation bonus for candidates joining us from a different city
• Employee Resource Groups (ERGs)