Sr. Machine Learning Engineer - LLMs & Generative AI

Pr. Machine Learning Engineer - LLMs & Generative AI Truveta is the world's first health provider-driven data platform with a vision of Saving Lives with Data. Our mission is to facilitate researchers to expedite the cure discovery, equip every clinician with expertise, and aid families in making informed care choices. Achieving Truveta's ambitious vision calls for a group of talented and inspired persons with a unique blend of health, software and big data experience and who share our company values. Truveta was founded in the Pacific Northwest, but we have employees nationwide. Our team appreciates the flexibility of a hybrid model and telecommuting. Being physically present is mandatory for two weeks in a year for Truveta Planning Weeks. For maximising productivity, our meeting hours align with the Pacific time zone. We avoid scheduling repeated meetings post 3pm PT, however, random meetings take place between 8 am-6 pm Pacific time. Who We Need We are on a lookout for an extremely motivated, experienced, and capable Machine Learning Engineer to join our AI research team and partake in our innovative Large Language Modeling (LLM) projects and clinical data analysis. Besides core capabilities, we are in search of problem solvers, enthusiastic and cooperative teammates, and those who are ready to do whatever it takes while making a difference. If purposeful work, being a part of a mission-driven team, and building a gratifying career while having fun interests you, Truveta might be the perfect place for you. This Opportunity We are seeking machine learning experts who can apply science and software development skills to create our Foundation Models that can help us solve some of the toughest problems in saving lives with data. You will work in a high-energy, fast-paced environment, collaborating closely with multiple teams across the company. You will be a part of an organization that brings together talents with diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine. Our team's versatility makes working here an exciting experience. We value and encourage diversity, believing that our differences make us and our products superior. In This Role, You Will: - Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications. - Use your expertise in machine learning and natural language processing to develop innovative algorithms and methodologies for generative modeling tasks. - Implement, train, and fine-tune LLM and GPT-like models on extensive 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 10 years of industry experience in the relevant fields). - Strong communication skills and the ability to work efficiently 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. This position presents a unique opportunity to work on cutting-edge language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare sector. Join us and make a significant impact on the future of healthcare and patient well-being. Why Truveta? Be a part of building something special. The perfect time to join Truveta is now. We have robust, established leadership with decades of success. We have ample funding. We are creating a culture that prioritizes people and their passions across personal, professional, and every aspect in between. Join us as we build an extraordinary company together. We Offer: - Interesting and significant work for every career stage - Great benefits package - Comprehensive benefits with robust 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) - The base pay for this position ranges from $192,000 to $260,000. The pay range reflects the minimum and maximum target. Pay is based on several factors.