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# Machine Learning Engineer

- **Company:** Truveta Inc.
- **Location:** Seattle, United States
- **Experience:** Experienced
- **Salary:** $155,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Health Informatics, Clinical Data Repository, Computer Clusters, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Tensorflow, Search Technologies, Software Engineering, Reinforcement Learning, Pytorch, Large Language Models, Scikit Learn, Information Technology, Machine Learning Operations, GPT
- **Published:** June 24, 2026
- **Apply:** https://www.dice.com/job-detail/4ef7ddcf-15c9-46e9-be17-ac17e0a1127f

## About the Role

Truveta is building a diverse and inclusive team to tackle complex health and technical challenges. We are seeking enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare. If you're excited about purposeful work, joining a mission-driven team, and launching your career in a supportive environment, Truveta could be the perfect place to start., * 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, * 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
 * Publications in top-tier ML conferences (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).
 * Experience building trustworthy AI systems and applying model interpretability, fairness, and safety frameworks.

## Description

* 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.


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