Senior Machine Learning Platform Engineer

Senior Machine Learning Platform Engineer

New York, NY

Why Charlie Health?

Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported.

Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection—between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home.

As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you.

About the Role

Charlie Health leads the nation in high-acuity virtual behavioral care, having delivered life-saving treatment to more than 100,000 clients nationwide. Our ML and AI capabilities are expanding rapidly—powering recommendation systems, clinical decision support, agentic AI products, and developer tooling—and the infrastructure underneath needs to scale with them.

As our first dedicated ML Platform Engineer, you'll define the technical direction and build the foundational systems that our data scientists, ML engineers, and product teams depend on to ship AI-powered features reliably and at scale. We have several models in production today and are investing in hosted GPU inference to support the next generation of our AI capabilities. You'll inherit and evolve existing infrastructure while building new platform capabilities—from multi-tenant model serving and GPU inference pipelines to multimodal data management, evaluation frameworks, observability, and infrastructure as code. You'll own the platform layer that makes ML/AI development at Charlie Health fast, safe, and repeatable as the team grows. If you care about building the systems that let others build great things, this team is for you.

Responsibilities

Infrastructure & Serving

• Define technical direction for ML/AI infrastructure and make build-vs-buy decisions as the founding platform engineer
• Design and operate multi-vendor AI infrastructure supporting client-facing and clinician-facing LLM applications across multiple LLM providers
• Design, build, and operate production model serving systems; maintain infrastructure as code for reproducible ML environments, training pipelines, and deployment workflows
• Develop high-performance GPU inference pipelines with low latency and high availability
• Own the multimodal data pipeline layer—manage ingestion, processing, and serving of text, audio, and structured clinical data for ML and AI systems

AI Systems & Tooling

• Create reliable infrastructure for agentic AI systems, including orchestration, monitoring, evaluation, and observability tooling
• Build developer tooling that accelerates data science and ML engineering workflows across the organization

Observability & Operations

• Own AI observability—build monitoring, alerting, and debugging capabilities for production ML systems
• Partner with ML engineers, data scientists, and product teams to understand infrastructure needs and translate them into scalable platform capabilities
• Foster a culture of collaboration and learning across engineering, product, and design through mentoring, documentation, presentations, and knowledge sharing
• Participate in our on-call rotation to ensure model serving uptime, pipeline reliability, and infrastructure health

Requirements

• 4+ years of professional experience in software engineering, with at least 2 years focused on ML infrastructure, ML platform, or AI systems engineering
• Strong software engineering fundamentals in Python and deep infrastructure expertise
• Familiarity with cloud ML services (AWS SageMaker, GCP Vertex AI, or similar) and CI/CD for ML pipelines
• Experience with infrastructure as code (Terraform, Pulumi, or similar) and container orchestration (Kubernetes, ECS)
• Experience building evaluation and observability systems for LLM-based or agentic AI applications is a plus
• Excellent at managing ambiguity—able to break down big, messy problems into smaller parts with tractable solutions and clear iterations
• Growth mindset and sense of humor; you welcome feedback, adapt quickly in a fast-paced environment, and foster a culture of learning and fun
• Experience with a systems language (Go, Rust, or C++) is a plus

This role requires 4 days per week in our NYC office (Flatiron District). The team is entirely based out of NYC.

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

The total target base compensation for this role will be between $170,000-$220,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits.

Our Values

• Connection: Care deeply & inspire hope.
• Congruence: Stay curious & heed the evidence.
• Commitment: Act with urgency & don't give up.