Truveta

Truveta is the world's first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta's ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. Truveta was born in the Pacific Northwest, but we have employees who live across the country. Our team enjoys the flexibility of a hybrid model and working from anywhere. In person attendance is required for two weeks during the year for Truveta Planning Weeks. For overall team productivity, we optimize meeting hours in the pacific time zone. We avoid scheduling recurring meetings that start after 3pm PT, however, ad hoc meetings occur between 8am-6pm Pacific time.

Who We Need

We are seeking a highly motivated, experienced, and talented Machine Learning Engineer to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In This Role, You Will

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

• Extensive software engineering experience in building high performance, large-scale ML systems (Preferably 3 to 5 years of industry experience in the relevant fields).
• Strong communication skills and the ability to work effectively in a collaborative research environment.
• Demonstrated leadership abilities, with experience in guiding and mentoring a team of ML engineers.
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems.
• Strong theoretical and practical background in NLP including experience with state-of-the-art LLM architectures optimized for handling large context and low inference cost.
• Advanced degree, ideally a Ph.D., in Computer Science, Electrical Engineering, or a related field with specialized research in areas such as machine learning, NLP, Large Language Models (LLMs), multi-modal foundation models, and generative AI techniques.
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI.
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code.

Preferred Qualifications

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models.
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques.
• Familiarity with training multi-modal foundation models and relevant frameworks.
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments.
• A track record of publications and contributions to the machine learning and natural language processing communities.

Why Truveta?

• Be a part of building something special.
• Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded.
• We are building a culture that prioritizes people and their passions across personal, professional, and everything in between.
• Join us as we build an amazing company together.

We Offer

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person as soon as we are able)

Compensation

The base pay for this position is $152,000 to $205,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

Diversity and Inclusion

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.