Machine Learning Engineer, Applied AI (Hybrid)

Machine Learning Engineer, Applied AI (hybrid)

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Purchasing a clean and concise rendering of SimplePractice’s mission and impact across the professional space. SimplePractice is committed to improving access to high‑quality care by providing clinicians with industry‑leading software, reducing administrative burden, and enabling solo or small‑group practitioners to thrive.

Recognized by MedTech Breakthrough as the Best Practice Management Solution Provider in 2024 and by the Digital Health Awards in 2023, SimplePractice is paving the future of health tech.

Título de sección: in Spanish The Role

Our team empowers Post-AIA clinicians through data‑driven innovations, combining rigorous data science with practical engineering to build systems that improve workflow efficiency and intuition. As a Machine Learning Engineer, Applied AI, you’ll create product features that help clinicians deliver quality care, from designing experiments and building robust models to tuning prompts, implementing LLM evaluation, and delivering end‑to‑end prototypes into production with product, engineering, and DevOps partners.

Responsibilities

• AI Prototyping & Development
  • Develop AI workflows, customize data pipelines, tune models, and engineer prompts to bring ideas to prototype.
  • Collaborate with subject matter experts to establish evaluation pipelines for AI workflows, ensuring rigor, quality, and safety of output.
  • Integrate AI workflows into production alongside engineering teammates.
  • Configure AI performance monitoring with reporting and alerting.
  • Optimize and maintain AI pipelines for performance, reliability, and long‑term scalability.
• Research
  • Begin with the Job‑to‑be‑Done, dive deep into the domain and view challenges from the user perspective.
  • Decompose problems into actionable components; design solutions using cross‑disciplinary thinking with a big‑picture view.
  • Conduct exploratory data analysis, design experiments, and build prototypes for proof‑of‑concept.
  • Create artifacts that illustrate findings rigorously and inform roadmap decisions.
• Cross‑Functional Collaboration
  • Provide AI expertise to product and engineering partners in shaping roadmaps.
  • Partner closely with team members from software, product, data engineering, and ML platform to scope, plan, and execute.
  • Communicate timelines, milestones, and findings to internal stakeholders.
• Mentor & Advocate Best Practices
  • Guide less experienced teammates, sharing knowledge on LLM workflows and the AI/ML model lifecycle.
• Drive Innovation
  • Stay current with emerging ML tools andneighbor technologies, integrating new techniques that enhance product capabilities.
  • Leverage data creatively to make clinicians’ lives easier, more efficient, and more effective.

Desired Skills & Experience

• BS or above in Computer Science, Statistics or a related technical field.
• 5+ years of experience in machine learning with a proven ability to bring ideas to production.
• Strong proficiency in Python and advanced data analysis tools.
• Strong data engineering skills, self‑sufficient in building pipelines for AI workflows.
• Experience deploying models on AWS (or other cloud platforms).
• Comfortable designing and evaluating LLM‑driven workflows.
• Familiarity with retrieval pipelines and vector databases.
• Strong problem‑oriented mindset with cross‑disciplinary thinking and simplicity bias.
• Experience working with remote teams using GitHub, Slack, Notion, Zoom.
• Proficiency in English with strong communication and collaboration skills.

Bonus Points

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• Experience with RAG architecture and context/state management for LLMs.
• Familiarity with LLM eval tools and human‑in‑the‑loop evaluation processes.
• Experience using Outerbounds or similar ML orchestration platforms.
• Experience with Argo Flows for CI/CD.
• Experience with prompt‑management tools like Langfuse.
• Familiarity with Kubernetes for container orchestration.
• Background in healthcare, clinical workflows, or regulated domains.ाषे .

Benefits

• Privatized Medical, Dental & Vision coverage.
• Work‑(node‑from‑home stipend.
• Flexible Time Off (FTO), wellbeing days, paid holidays, and Summer Fridays.
• Monthly meal reimbursement.
• Holiday bonus_tc 15‑day Aguinaldo.
• Hybrid work schedule & catered lunch.
• Relocation TRANSACTION for candidates joining from a different city.
• Employee resource groups (ERGs).

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Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Engineering and Information Technology
Industries: Software Development

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