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SimplePractice

Senior Machine Learning Engineer

Sorry, this job was removed at 06:19 p.m. (MST) on Monday, Aug 04, 2025
Easy Apply
Remote
Hiring Remotely in United States
Easy Apply
Remote
Hiring Remotely in United States

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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, you’ll be at the forefront of using data to shape and optimize clinician workflows. Your day-to-day will blend creative problem-solving with hands-on technical work—designing experiments, building robust models, and collaborating with cross-functional teams to bring new ideas to life. You’ll be instrumental in guiding data initiatives that drive our product roadmap, helping us create intuitive features and tools that clinicians rely on every day.

You’ll also 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. Whether you’re fine-tuning a model, presenting insights to stakeholders, or brainstorming new product features, your work will have a direct and meaningful impact.

Key Responsibilities

  • Develop & Deploy ML Pipelines
    • Build end-to-end solutions—from data exploration to model deployment—that enhance clinician experiences
    • Optimize and maintain models for performance, reliability, and long-term scalability
  • Lead Advanced Analysis
    • Conduct deep-dive analyses, uncovering insights that drive product decisions
    • Collaborate with product teams to turn data into actionable next steps
  • Cross-Functional Collaboration
    • Work closely with Engineering, Product, and Design to ensure ML features are intuitive, impactful, and aligned with clinician needs
    • Communicate complex results clearly to both technical and non-technical partners
  • Mentor & Advocate Best Practices
    • 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
  • Drive Innovation
    • 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 

  • Proficiency in Python (NumPy, Pandas, scikit-learn)
  • Strong skills in SQL (window functions, advanced queries)
  • Hands-on experience with DBT for data transformation
  • Familiarity with Snowflake or similar data warehouses
  • Experience with AWS (or other cloud platforms) for model deployment

Bonus Points 

  • Exposure to Outerbounds or similar ML orchestration platforms
  • Experience with Argo Flows for CI/CD
  • Familiarity with Kubernetes for container orchestration

Base Compensation Range

$150,000 - $200,000 annually

Base salary is one component of total compensation. Employees may also be eligible for an annual bonus or commission. Some roles may also be eligible for overtime pay.

The above represents the expected base compensation range for this job requisition. Ultimately, in determining your pay, we’ll consider many factors including, but not limited to, skills, experience, qualifications, geographic location, and other job-related factors.

Benefits

We offer a competitive benefits program including:

  • Medical, dental, vision, life & disability insurance
  • 401(k) plan with company match
  • Flexible Time Off (FTO), wellbeing days, paid holidays, and summer Fridays
  • Mental health resources
  • Paid parental leave & Backup Care
  • Tuition reimbursement
  • Employee Resource Groups (ERGs)

California Job Applicant Privacy Notice

Thank you for your interest in opportunities at SimplePractice LLC (“SimplePractice” or “us” or “we” or “our”). Please note that when you submit your resume or application materials to us for employment purposes, you are subject to the SimplePractice California Job Applicant Privacy Notice. 

For more information about our privacy practices, please contact us at [email protected].

SimplePractice Colorado, USA Office

CO, United States

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

  • Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
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  • Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
  • Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
  • Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

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