Senior AI Platform Engineer
Twin Health · United States
- Hybrid
- Full-time
- $190,000 / year
- United States
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Job highlights
- Build robust AI/ML systems for production.
- Lead cross-functional ML initiatives.
- Optimize ML model workflows and lifecycle.
- Ensure operational excellence of ML systems.
- Mentor team and share knowledge.
About the role
About Twin Health
Twin Health empowers people to improve and prevent chronic metabolic diseases, like type 2 diabetes and obesity, with a new standard of care. Twin Health is the only company applying AI Digital Twin technology exclusively toward metabolic health. We start by building a dynamic model of each person’s metabolism — drawing on thousands of data points from CGMs, smartwatches, and meal logs — that maps their personal path to better health. Guided by a dedicated clinical care team, our members have lowered their A1C below the diabetes range, achieved lasting weight loss, and reduced or even eliminated medications, all while living healthier, happier lives.Working at Twin Health
Our team at Twin Health is passionate, talented, and united by a shared purpose: to improve the metabolic health and happiness of our members. We believe in empowering every Twin to make a meaningful impact for our members, our clients, and each other, while enjoying a supportive, collaborative work environment. Twin has been recognized not only for our innovation but also for our culture, including: Innovator of the Year by the Employer Health Innovation Roundtable (EHIR), selected to CB Insights’ Digital Health 150, and named one of Newsweek’s Top Most Loved Workplace®. With more than $100 million raised in recent funding, including a $53 million Series E round in 2025 led by Maj Invest, and a $50 million investment in 2023 led by Temasek, Twin is scaling rapidly across the U.S. and globally. Backed by leading venture firms like ICONIQ Growth, Sequoia, Sofina, Temasek, and Peak XV, we are building the most impactful digital health company in the world. Join us as we reinvent the standard of care in metabolic health.Opportunity
Are you ready to be at the forefront of integrating machine learning with healthcare technology? We are seeking a dynamic and innovative ML Ops Engineer. The ideal candidate is self-driven, versatile in handling multiple projects, and a collaborative team player. You will be instrumental in developing our cutting-edge machine learning platform and enhancing our existing healthcare solutions. We value individuals who are adept at working with complex systems and possess exceptional communication and leadership skills.Responsibilities
- Architect, design, and build robust and efficient AI/ML systems for a production environment, focusing on backend distributed systems, microservices, and ensuring system accuracy.
- Lead cross-functional initiatives end-to-end (scoping, timelines, dependencies), driving alignment across Data, Infra and ML Engineering.
- Collaborate closely with AI/ML engineers to optimize workflows for model training, real-time inference, monitoring, and troubleshooting.
- Be a subject matter expert on ML infrastructure, providing guidance to both internal teams and external stakeholders.
- Ensuring operational excellence and reliability of ML systems. Define and enforce SLAs around system performance, including latency, throughput, and resource utilization.
- Develop tools for effective model management, continuous monitoring, and enhancing the efficiency and effectiveness of the entire ML lifecycle.
- Actively engage in mentorship and knowledge sharing to promote a culture of continuous learning and improvement within the team.
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field with 5+ years of industry experience.
- Familiarity with architectural frameworks of large, distributed, and high-scale ML applications. Experience in the implementation of applications using LLM’s and GenAI is a huge plus.
- Solid understanding of MLOps, data structures, and software design principles.
- Proficiency in programming with Python and experience in other languages like Java or Go.
- Strong knowledge in deploying scalable machine learning models, including experience with Docker, Kubernetes, and microservices architecture.
- Experience with database technologies (e.g., SQL, NoSQL) and big data processing frameworks (e.g., Spark) is a plus.
Key skills/competency
- AI/ML Systems Engineering
- Production ML Environments
- Distributed Systems
- Microservices Architecture
- MLOps
- Model Training and Inference
- Monitoring and Troubleshooting
- LLMs and GenAI
- Python
- Docker and Kubernetes
Skills & topics
- AI Platform Engineer
- MLOps Engineer
- Machine Learning
- AI
- Python
- Distributed Systems
- Microservices
- Kubernetes
- Docker
- Healthcare Technology
- Digital Health
- Senior Engineer
How to get hired
- Tailor your resume: Highlight your experience with AI/ML systems, MLOps, Python, Docker, and Kubernetes to match Twin Health's needs.
- Showcase relevant projects: Emphasize your contributions to large-scale ML applications, distributed systems, and microservices architecture.
- Demonstrate leadership: Provide examples of leading cross-functional initiatives and mentoring teams.
- Prepare for technical interviews: Be ready to discuss ML infrastructure, system design, and coding challenges.
- Understand Twin Health's mission: Articulate how your skills can contribute to their goal of improving metabolic health.
Technical preparation
Master Python for ML development.,Practice Docker and Kubernetes deployments.,Study distributed systems and microservices.,Understand MLOps principles and workflows.
Behavioral questions
Describe leading a complex project.,How do you mentor junior engineers?,Explain resolving production ML issues.,How do you collaborate with diverse teams?
Frequently asked questions
- What is the role of an AI Platform Engineer at Twin Health?
- As a Senior AI Platform Engineer at Twin Health, you will be responsible for architecting, designing, and building robust AI/ML systems for production environments. This includes focusing on backend distributed systems, microservices, optimizing model training and inference workflows, ensuring operational excellence, and providing subject matter expertise on ML infrastructure. You will also lead cross-functional initiatives and mentor team members.
- What technical skills are most important for this Senior AI Platform Engineer role at Twin Health?
- Key technical skills for this role include proficiency in Python, experience with deploying scalable machine learning models using Docker and Kubernetes, and a strong understanding of MLOps, data structures, and software design principles. Familiarity with LLMs, GenAI, distributed systems, microservices architecture, SQL/NoSQL databases, and big data processing frameworks like Spark are also highly valued.
- Does Twin Health require experience with LLMs and GenAI for the Senior AI Platform Engineer position?
- While not strictly required, experience in the implementation of applications using LLMs and GenAI is considered a significant plus for the Senior AI Platform Engineer role at Twin Health. It indicates a forward-thinking candidate with relevant, in-demand skills for modern AI platforms.
- What kind of professional background is Twin Health looking for in a Senior AI Platform Engineer?
- Twin Health is looking for candidates with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, coupled with at least 5 years of industry experience. A proven track record in architecting and building large-scale, distributed ML applications and a solid understanding of MLOps principles are essential.
- How does Twin Health approach remote work for its Senior AI Platform Engineer roles?
- Twin Health offers a remote work arrangement for its employees, including the Senior AI Platform Engineer position. This allows for a globally distributed team, providing flexibility and access to a diverse talent pool.
- What is the compensation range for the Senior AI Platform Engineer role at Twin Health?
- The compensation for the Senior AI Platform Engineer position at Twin Health is in the range of $180,000 to $200,000 annually.
- What are the benefits offered to employees at Twin Health?
- Twin Health offers a competitive compensation package, unlimited vacation with manager approval, 100% paid parental leave (16 weeks for delivering parents, 8 weeks for non-delivering parents), and 100% employer-sponsored healthcare, dental, and vision for employees (with 80% coverage for family). They also provide 401k retirement savings plans and opportunities for equity participation.
- How can I prepare for the technical interview for the Senior AI Platform Engineer role at Twin Health?
- To prepare for the technical interview at Twin Health, focus on solidifying your understanding of MLOps principles, distributed systems design, microservices architecture, and scalable model deployment strategies using tools like Docker and Kubernetes. Practice coding problems in Python, and be ready to discuss your experience with large-scale ML applications and how you've ensured operational excellence in production environments.