Machine Learning Engineer, Applied AI (Hybrid)
SimplePractice
Full-time|Hybrid|Mexico City About Us At SimplePractice, we are committed to enhancing access to high-quality healthcare by providing health and wellness professionals with comprehensive tools designed for success in private practice. With over 250,000 providers relying on SimplePractice, our state-of-the-art software offers powerful solutions that streamline every aspect of practice management. From administrative tasks to clinical care, our suite of innovative tools works harmoniously to alleviate the administrative load, enabling solo and small group practitioners to flourish alongside their clients. Awarded the title of Best Practice Management Solution Provider by MedTech Breakthrough in 2024 and recognized in the Digital Health Awards in 2023, SimplePractice is dedicated to shaping the future of health technology. The Role Join our team focused on empowering clinicians through data-driven innovations. We merge advanced data science with practical engineering to create systems that enhance daily workflows, making them more efficient and insightful. If you thrive on solving complex challenges and transforming data into impactful results, you will find a dynamic and supportive environment here. As a Machine Learning Engineer specializing in Applied AI, you will play a crucial role in developing product features that enable clinicians to deliver effective and efficient patient care. Your responsibilities will include designing experiments, constructing robust models, fine-tuning prompts, implementing LLM evaluations, and guiding projects from conception to prototype and production in collaboration with product, engineering, and DevOps teams. Additionally, you will contribute significantly to the strategic planning of our ML platform. We foster a culture of mentorship, open dialogue, and exploration of AI’s potential in real-world healthcare applications. Whether you are optimizing a model, sharing insights with stakeholders, or brainstorming new product features, your contributions will have a direct and substantial impact. Responsibilities AI Prototyping and Development Create AI workflows, customize data pipelines, refine models, and design prompts to bring ideas to prototype. Collaborate with subject matter experts to establish evaluation criteria for AI workflows, ensuring quality, safety, and reliability of outputs. Partner with engineering teams to integrate AI workflows into production environments. Develop and configure AI performance monitoring systems with appropriate reporting and alert systems. Optimize and sustain AI workflows for performance, dependability, and long-term scalability. Research Begin with the Job-to-be-done framework, deeply exploring the domain to understand challenges from the user’s perspective.
Apr 13, 2026