Senior Machine Learning Engineer, Platform (hybrid)

Job description

Overview

Senior Machine Learning Engineer, Platform (hybrid)

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About Us

At SimplePractice, our team is dedicated to improving the health and wellness industry by building a suite of innovative solutions for practitioners and their clients.

Our product supports practitioners on their clinical journey to becoming licensed, helps them manage their business and practice once they’re up and running, and enables new clients to discover and interact with practitioners.

Taking a practitioner-first approach in everything we do makes it possible for health and wellness practitioners to devote more time to their clients while they use SimplePractice to start, grow, and maintain a successful private practice.

The Role

Our team is dedicated to empowering clinicians through data-driven innovations.

We combine rigorous data science with practical engineering to build systems that make daily workflows more efficient, insightful, and intuitive.

Our responsibilities span everything from data ingestion and transformation to advanced ML model deployment—ensuring clinicians have the right information at the right time to deliver exceptional care.

We thrive on curiosity, collaboration, and continuous learning.

By working closely with Product, Design, and Engineering, we aim to create solutions that genuinely enhance clinician experiences.

If you love tackling challenging problems and turning data into meaningful outcomes, you’ll find a welcoming and dynamic environment here.

As a Senior Machine Learning Engineer, Platform , you’ll be at the forefront of building tools and systems for AI engineers and developers to innovate rapidly and responsibly.

Your day-to-day will blend creative problem-solving with hands-on technical work—building systems that are robust, scalable and easy to maintain, as well as working with target users with empathy, contributing to the roadmap exercise of ML Platform.

You’ll also play an important role in the technical vision and architecture of the ML Platform and have plenty of chances to sharpen and share your expertise.

We value mentorship, open communication, and pushing the boundaries of what ML can do in a real-world healthcare context.

Key Responsibilities

• Develop & Deploy ML Platform
  • Build end to end solutions to ensure consistent tooling and governance for LLM/AI feature development
  • Ability to design well-structured and performant RESTful APIs, including defining clear endpoints, request/response formats, and error handling
• Cross-Functional Collaboration
  • Work closely with Engineering, and other internal stakeholders of ML platform to develop platform roadmap
  • Properly communicate timeline, milestones, and progress w/ internal stakeholders
  • Drive stakeholder engagement, enablement and education to ensure the platform is well integrated into AI dev workflow
• Guide less experienced team members, sharing knowledge on model development, MLOps, and data engineering
• Champion a culture of experimentation, continuous learning, and proactive problem-solving
• Stay current with emerging ML tools and technologies, integrating new techniques that elevate our product capabilities
• Look for creative ways to leverage data to make clinicians’ lives easier, more efficient, and more effective

Desired Skills & Experience

• BS or above in Computer Science or a related technical field
• 7+ years of experience in software development, ideally on dev tools, with Python expertise for a part of your career
• Have experience with ML/LLM.
  
  Familiar with ML model workflow, from ideation, prototyping to deployment
• Proficiency in building data pipelines and tooling for ML feature pipelines
• Experience with AWS (or other cloud platforms) for model deployment
• Comfort working with remote teams, using GitHub, Slack, Notion, and Zoom
• Proficiency in English with strong communication and collaboration skills

Bonus Points

• Experience with RAG architecture and other LLM design patterns
• Experience with pythonic asynchronous tools like Celery
• Exposure to Outerbounds or similar ML orchestration platforms
• Experience with Argo Flows for CI/CD
• Familiarity with Kubernetes for container orchestration

Benefits

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

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Candidates from all backgrounds are encouraged to apply.

Required Skill Profession

Redes Y Sistemas