Machine Learning Engineer - LLMs & Generative AI

Who We Need

We are seeking enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare.

Responsibilities

• Lead the development, training, and deployment of large language and multimodal foundation models tailored to clinical and biomedical domains.
• Apply and refine state-of-the-art techniques such as supervised fine-tuning (SFT), reinforcement learning-based methods (e.g., RLHF, RLVR), parameter-efficient fine-tuning (PEFT), prompt tuning, and retrieval-augmented generation (RAG).
• Collaborate cross-functionally with researchers, clinicians, and engineers to design ML-driven solutions that improve healthcare delivery and outcomes.
• Build scalable infrastructure for distributed training of large models (TPU/GPU clusters, multi-node orchestration).
• Design and evaluate models for robustness, bias mitigation, factual consistency, and explainability in healthcare contexts.
• Stay current with the latest research in generative AI and contribute back to the community through publications and open-source initiatives.

Minimum Qualifications

• 6+ years of experience in software engineering or machine learning (3+ years with a PhD).
• Experience designing and training LLMs or large-scale generative models (e.g., GPT, PaLM, LLaMA, Claude, Gemma).
• Deep expertise in NLP, sequence modeling, and transformer architectures.
• Proficient in Python and ML libraries such as PyTorch or TensorFlow; strong engineering skills in building scalable ML pipelines.
• Experience with RL-based fine-tuning (e.g., Reinforcement Learning from Human Feedback) and evaluation of generative systems.
• Proven ability to lead technical projects and collaborate across teams.
• Bachelor's degree in Computer Science, Engineering, or a related technical field

Preferred Qualifications

• PhD or equivalent experience in Machine Learning, NLP, AI, or a related field.
• Experience in healthcare, biomedical informatics, or clinical data modeling.
• Familiarity with multi-modal foundation models (e.g., text-image, text-structured data) and cross-modal alignment techniques.
• Hands-on experience with vector databases, semantic search, and retrieval-based generation.
• Publishations in top-tier ML conferences (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).
• Experience building trustworthy AI systems and applying model interpretability, fairness, and safety frameworks.

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
• A great benefits package
• A comprehensive benefits with strong medical, dental and vision insurance plans
• A 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• A generous parental leave
• Regular team activities (virtual and in-person)

Pay Range

The base pay for this position is $155,000 to $175,000. 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.