Senior Applied AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the technical implementation of intricate AI projects, taking ownership of the design and delivery of solutions within a specific product or technical domain while collaborating with senior engineers on overarching architectural direction.

• Design, develop, train, assess, and enhance advanced machine learning and LLM-based systems for products aimed at patients and providers (e.g., conversational AI, personalization, user insights, clinical decision support, chronic care management).

• Manage problems comprehensively: define the issue with clinicians and product partners, construct datasets and evaluations, iterate on modeling, and deploy to production with appropriate monitoring and safeguards.

• Establish robust evaluation frameworks — including offline benchmarks, human-in-the-loop assessments, and online experiments — that ensure our models are safe, accurate, and progressively improving.

• Develop and enhance the platform that enables the team to operate efficiently: data pipelines, training and inference infrastructure, prompt and model management, and tools for clinical reviewers.

• Collaborate closely with clinicians, product teams, and engineers to convert medical and operational requirements into ML challenges and deliver measurable enhancements to the experiences of patients and clinicians.

• Define the technical trajectory for your area, mentor fellow engineers, and elevate the standards of engineering and scientific rigor. The extent of leadership expands with seniority.

• Remain engaged with current literature and the rapidly changing AI landscape; bring back insights that are most beneficial for our patients and our team.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Mathematics, or a related technical field.

• Over 3 years of hands-on engineering experience, with at least 1 year dedicated to building and deploying machine learning systems, including generative AI (LLMs), demonstrating a clear track record of impact.

• Strong foundation in software engineering principles and the capacity to deliver reliable, well-tested code in Python (or a similar language) within a production environment.

• Practical knowledge of contemporary LLM techniques: prompting, retrieval-augmented generation, fine-tuning, evaluation, and understanding the trade-offs involved.

• Ability to work comfortably with messy, real-world data and design evaluations to ascertain whether a system is functioning effectively.

• Excellent written and verbal communication skills; capable of collaborating across disciplines with clinicians, product managers, and engineers.

• A proactive approach and sense of ownership: able to tackle ambiguous problems, drive them to resolution, and engage others in the process.

• Passion for the mission. You aspire for your work to contribute to improved health outcomes for real patients.

• Nice to Have:

• Experience implementing ML or LLMs in healthcare, life sciences, or other regulated, high-stakes environments.

• Background in clinical NLP, medical knowledge representation, or working with electronic health record data.

• Experience in building agentic systems and tool-using LLMs in production settings.

• Experience in scaling ML infrastructure — including training pipelines, distributed inference, and evaluation platforms — for a small, agile team.

• Proven track record of technical leadership: setting direction across teams, mentoring engineers, or publishing impactful work.

🏝️ Benefits

• Comprehensive medical, dental, and vision coverage.

• Flexible spending plans.

• Generous and adaptable Paid Time Off (PTO), floating holidays, and parental leave.

• 401k plan with employer matching.

• 100% remote — work from home.