Truveta: ML Postdoc Researcher - Healthcare AI Innovation — Seattle, WA

About Truveta

Truveta is a health-data and analytics company. It aggregates de-identified electronic health record data from a network of United States health systems into a research dataset for studying treatments, outcomes and patient care pathways, serving life-science and health researchers. The platform is owned and governed by the participating health systems, and its employer feed lists engineering, data and clinical roles supporting the work.

The position and its setting

Truveta lists ML Postdoc Researcher - Healthcare AI Innovation in Seattle, WA, under reference 5978375004. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Internship
• Employer listing date: 22 April 2026

Responsibilities and work described

• " data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Innovate: Identify and propose novel, high-impact applications of AI/ML using large-scale EHR data
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Research & Prototype: Design, develop, and evaluate state-of-the-art models (e.g., foundation models, multimodal learning, causal ML, generative AI)
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Work Across Modalities: Integrate structured and unstructured EHR data with emerging data types such as genomics, imaging, and clinical notes
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Collaborate Cross-Functionally: Partner with clinicians, data scientists, and product teams to translate research ideas into real-world solutions
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Publish & Share: Contribute to top-tier conferences/journals and represent Truveta in the research community
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Explore the Unknown: Proactively identify problems that have not yet been addressed and define new research directions

Essential requirements and candidate background

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• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Curious and imaginative: You naturally think beyond existing solutions and ask “what hasn’t been done yet?”
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Impact-driven: You care about applying research to real-world healthcare problems
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Comfortable with ambiguity: You thrive in open-ended environments where defining the problem is part of the job
• ","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"> Collaborative: You enjoy working across domains and learning from experts in different fields
• 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

Preferred experience and additional strengths

• Experience: healthcare data (EHRs, claims, clinical notes) or biomedical data (genomics, imaging)
• Familiarity: cutting-edge areas such as:
• Foundation models / LLMs in healthcare
• Multimodal learning
• Causal inference
• Representation learning on longitudinal data
• Track record of publications in top-tier ML or healthcare venues (e.g., NeurIPS, ICML, ICLR, MLHC, AMIA)
• Work across disciplines and communicate with both technical and clinical stakeholders
• 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

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Advertised location: Seattle, WA

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another ML Postdoc Researcher - Healthcare AI Innovation vacancy is not an offer for reference 5978375004; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Truveta

Applications follow the official employer page linked below.

Open the official Truveta posting below and match the title and reference 5978375004.

Compare your qualifications and experience with the essential conditions for the Seattle, WA position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: machine learning

For machine-learning work, describe the problem, the data and the evaluation setup. Explain the baseline, the metric and the part you owned; mention deployment or monitoring only when you worked on it.

Relevant skills

• AI/ML
• LLMs
• machine learning
• AI
• clinical research
• stakeholder management
• claims administration