Research Engineer Applied ML AI
@ Sully.ai

Hybrid
$150,000
Hybrid
Full Time
Posted 8 hours ago

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Job Details

About Sully.ai

Our team comes from OpenAI, DeepMind, NASA, GoogleX, Tesla, and includes 2 physicians. With 6 exits, 2 IPOs, our model outperforms Claude, Gemini, and GPT-4.5 on clinical benchmarks and we have partnered with 400+ healthcare organizations in 16 months. We have raised $25M from YC, Amity Ventures, Sequoia scouts, among others and are targeting a $1T+ market opportunity.

About the Role

The Research Engineer Applied ML AI will bridge cutting-edge research and scalable production systems by owning training, fine-tuning, and inference toolchains. The role involves driving multimodal (text, audio, vision) integration and optimizing model throughput and evaluation in production. You will ensure Sully.ai's research artifacts translate into stable, high-performance features powering our healthcare agents.

Key Responsibilities

  • Own full training, fine-tuning, and inference toolchains.
  • Translate research repositories into production-ready services with stable APIs.
  • Ship multimodal features (text, audio, vision) to boost agent performance.
  • Optimize inference pipelines for cost, throughput, and latency.
  • Build evaluation systems integrated into CI/CD to block weak checkpoints.

Hard Requirements

  • Strong engineering background with experience in distributed systems and large-scale model training/serving.
  • Hands-on experience with multimodal ML (audio, vision, text).
  • Experience with production ML hygiene: versioning, metrics, observability, reproducibility.
  • Proven track record of shipping ML systems into production.

Nice-to-Have

  • Experience with model optimization techniques such as quantization, caching, pruning.
  • Background in healthcare, medical AI, or other high-stakes regulated environments.
  • Contributions to open-source ML frameworks or libraries.

First-Month Focus

  • Audit and streamline current training, fine-tune, and inference pipelines.
  • Stand up evaluation frameworks that gate deployments in CI.
  • Deliver first improvements in throughput, cost, or latency of deployed models.

Success OKRs (90 Days)

  • Deploy at least one multimodal feature (speech or vision) to production agents.
  • Reduce inference cost or latency by 30% via optimization strategies.
  • Integrate evaluation guardrails into CI/CD to block underperforming model releases.

Culture Fit

  • Persistent, driven problem solver.
  • Willing to push back on leadership to defend quality/timelines.
  • Thrives in high-ambiguity, fast-paced startup environments.

Why Join Sully.ai?

  • Shape the Future of Healthcare by building impactful partnerships.
  • Enjoy early-stage impact and a key role in company growth.
  • Remote-first culture with a flexible, mission-driven team.
  • Competitive compensation including salary, equity, and growth opportunities.
  • Solve scalability challenges in a rapidly growing company.

Key Skills/Competency

  • ML Engineering
  • Production ML
  • Multimodal Integration
  • Distributed Systems
  • API Development
  • CI/CD
  • Pipeline Optimization
  • Inference Systems
  • Model Training
  • Healthcare AI

How to Get Hired at Sully.ai

🎯 Tips for Getting Hired

  • Research Sully.ai culture: Understand their mission, team, and projects.
  • Customize your resume: Highlight distributed systems and ML production skills.
  • Showcase multimodal experience: Include text, audio, vision projects.
  • Prepare for technical interviews: Practice ML and system optimization challenges.

📝 Interview Preparation Advice

Technical Preparation

Review distributed systems concepts.
Practice ML model training and deployment.
Study multimodal integration techniques.
Optimize inference pipelines using benchmarks.

Behavioral Questions

Describe a challenging project experience.
Explain teamwork in fast-paced environments.
Share examples defending timelines.
Discuss handling ambiguous project requirements.

Frequently Asked Questions