About Us:
Ambience Healthcare is the leading AI platform for documentation coding and clinical workflow built to reduce administrative burden and protect revenue integrity at the point of care. Trusted by top health systems across North America Ambiences platform is live across outpatient emergency and inpatient settings supporting more than 100 specialties with real-time coding-aware documentation. The platform integrates directly with Epic Oracle Cerner athenahealth and other major EHRs. Founded in 2020 by Mike Ng and Nikhil Buduma Ambience is headquartered in San Francisco and backed by Oak HC/FT Andreessen Horowitz (a16z) OpenAI Startup Fund Kleiner Perkins and other leading investors.
Join us in the endeavor of accelerating the path to safe & useful clinical super intelligence by becoming part of our community of problem solvers technologists clinicians and innovators.
As a Staff Research Engineer at Ambience you will push the boundaries of generative AI by translating cutting-edge research into working prototypes and experimental platforms. Youll work closely with fellow researchers engineers and product leads to explore novel architectures fine-tuning methods evaluation paradigms and data strategieshelping to define whats possible with frontier AI models.
Our engineering roles are hybrid working onsite at our San Francisco office three days per week.
Prototype and Advance LLM Systems: Build and benchmark LLM-based systems and agents using open-source and proprietary models. Rapidly prototype new capabilities through fine-tuning adapters and reinforcement learning approaches.
Drive Research-First Experimentation: Translate recent academic papers into reproducible experiments focusing on fine-tuning (e.g. LoRA QLoRA DPO) model alignment and hallucination mitigation techniques. Design clear experiment plans and share findings across the team.
Build and Evolve Evaluation Pipelines: Define evaluation methodologies using human-in-the-loop feedback synthetic benchmarks and task-specific metrics. Implement continuous evaluation pipelines to track regressions and breakthroughs.
Shape Data and Training Strategy: Curate datasets via synthetic generation targeted scraping and annotation pipelines. Establish practices for discovering failure cases and improving model robustness over time.
Contribute to a Research-Driven Culture: Write research papers internal memos and blog posts. Foster a culture of experimentation documentation and knowledge-sharing across research and engineering teams.
Research Fluent
Skilled at interpreting and replicating results from cutting-edge machine learning research.
Experienced in designing experiments running ablation studies and ensuring reproducibility.
4 years of experience in machine learning research experimental AI or applied AI engineering.
Demonstrated ability to replicate extend or publish original research.
Deep Expertise in LLM Fine-Tuning
Hands-on experience fine-tuning large language models and optimizing prompt and embedding strategies.
Proficient with Python and deep learning frameworks such as PyTorch JAX and Hugging Face Transformers.
Comfortable with distributed training environments and large-scale model experimentation.
Evaluation and Data Obsessed
Deep understanding of dataset curation filtering and alignment with evaluation goals.
Familiar with human annotation pipelines ranking models (e.g. RM RLAIF) and interpretability techniques.
Experienced in building evaluation frameworks tied to real-world task performance.
Collaborative and Curious
Thrives in research-driven environments with a commitment to experimentation documentation and cross-functional learning.
Excited to prototype present findings and build at the frontier of AI advancement.
Effective Interdisciplinary Collaborator
Able to work alongside clinicians product managers and fellow engineers
Strong communicator who can distill complex ML concepts for diverse audiences.
Mission-Aligned
Passion for healthcare or other mission-driven industries (e.g. education climate tech)
Thrives in a fast-paced early-stage environment; takes extreme ownership of deliverables
Nice-to-haves
Open-source contributions to ML libraries datasets or benchmarks
Experience working in AI research labs frontier model companies or early-stage AI startups
Background in RLHF alignment research or AI safety
$250000 - $350000 with the addition of significant equity.
Are you outside of the range We encourage you to still apply; we take an individualized approach to ensure that compensation accounts for all of the life factors that matter for each candidate.
Being at Ambience:
An opportunity to work with cutting edge AI technology on a product that dramatically improves the quality of life for healthcare providers and the quality of care they can provide to their patients
Dedicated budget for personal development including access to world class mentors advisors and an in-house executive coach
Work alongside a world-class diverse team that is deeply mission aligned
Ownership over your success and the ability to significantly impact the growth of our company
Competitive salary and equity compensation with benefits including health dental and vision coverage quarterly retreats unlimited PTO and a 401(k) plan
Ambience is committed to supporting every candidates ability to fully participate in our hiring process. If you need any accommodations during your application or interviews please reach out to our Recruiting team at . Well handle your request confidentially and work with you to ensure an accessible and equitable experience for all candidates.
Required Experience:
Staff IC