Senior Machine Learning Engineer

1 Month ago • 5-7 Years • Research Development • $210,000 PA - $225,000 PA

Job Summary

Job Description

As a Senior Machine Learning Engineer at Suki, you will be at the core of product innovation, utilizing your NLP expertise to enhance computational infrastructure and improve algorithms. You will work directly on the platform powering microservices and collaborate with cross-functional teams to address NLP challenges. Your responsibilities will include managing and curating large datasets, monitoring system performance, and staying updated on NLP advancements. This role offers an opportunity to significantly impact the lives of clinicians by reducing their administrative burdens.
Must have:
  • 5-7+ years of Machine Learning experience, with 3+ in NLP
  • Proven record of end-to-end workflow and NLP model deployment
  • Expertise in deep neural network models
  • Ability to build and maintain distributed backend services

Job Details

The Future of Healthcare Needs You

At Suki, we’re building technology that listens, understands, and gets out of the way — so clinicians can get back to being clinicians.

Our flagship product, Suki Assistant, uses cutting-edge AI to automate clinical documentation in real time, reducing the time it takes to complete notes by 72%. But that’s just the beginning.

We’re now powering the next wave of voice-enabled healthcare experiences across telehealth platforms, care delivery tools, and specialty EMRs — through Suki Platform, our proprietary AI infrastructure.

Clinicians using Suki spend over 70% less time on admin. Our customers see a 9X ROI in year one. And we’re just getting started.

Suki is reimagining the healthcare technology stack to make the lives of clinicians better.

Our tech stack includes GCP, Kubernetes, Vertex AI, Golang, Python, C++, PyTorch, JAX, Transformers, GPT, LLAMA, MoE, gRPC, Javascript.

What We’re Trying to Do (And Why We Need You)

We’re not here to tweak healthcare around the edges — we’re rearchitecting it. 

That’s where you come in.

The Machine Learning team forms the core of Suki's product, driving innovation and excellence. You'll leverage your NLP expertise to enhance our computational infrastructure and improve processes and algorithms. Working directly on the platform powering our microservices, you'll collaborate with cross-functional teams to address NLP challenges and scale our platform for thousands of doctors. You'll manage and curate large datasets, ensuring data quality and relevance for training and evaluation. You'll monitor and analyze system performance metrics, identifying areas for optimization and implementing necessary improvements. By staying updated on NLP advancements, you'll incorporate innovations to maintain our competitive edge, reducing doctors’ administrative burdens and significantly impacting their daily lives.  

Ok, you're sold, but what are we looking for in the perfect candidate?

  • Expertise: You know how to code.  You understand our tech stack and can be productive with it. In other words, you’ve done this before.
  • Action oriented: You love to build.  You like to ship fast and quickly iterate.
  • Creativity: You enjoy listening to user feedback and then building products in novel ways. You’re resourceful and enjoy finding alternate paths to success.
  • Problem solving: you use data to help point you in the correct direction. You optimize relentlessly.  You think business and engineering problems are like puzzles and you stick with them until they are solved.
  • Humility: You’re humble and love working in a team without ego to deliver products
  • Adaptability:  You thrive in a fast-moving organization that uses light-weight processes and cutting-edge technology to have a huge impact.
  • Confidence: You trust your abilities and you’re ready to push yourself to the next level.

Requirements:*

  • 5-7+ years in overall Machine Learning experience, with at least three years focused on NLP
  • Proven record of an end to end workflow and with moving at least one NLP model to an enterprise production system
  • Expert in the understanding, practice, and deployment of state-of-the-art deep neural network models
  • Proven ability to build and maintain distributed backend services for ML/AI Applications
  • Strong grasp of CS fundamentals including algorithms, data structures and design is preferred
  • You will be required to work onsite M-F.

*Requirements is such a strong word. We don’t necessarily expect to find a candidate that has done everything we’ve listed, but you should be able to make a credible case that you’ve done most of it and are ready for the challenge of adding some new things to your resume.

What Makes Suki, Suki

  • A mission that matters: Suki is making healthcare technology invisible and assistive—so clinicians can focus fully on patient care.
  • A product that delivers: Our AI is used by real clinicians at real health systems — and it works.
  • A team that gets it: We’re former Googlers, Apple engineers, Stanford docs, and healthcare veterans.
  • Backed by believers: We’ve raised $165M from top VCs like Venrock, First Round, Flare, and March Capital.
  • On a roll: Named by Fast Company as the Next Big Thing in Tech. Best Leadership Team by Comparably. Technology Innovation Award by Frost & Sullivan.
  • Massive market: We’re disrupting a $30B+ industry, and our momentum is real.

More Than Just a Job

You’ll join a team of mission-driven builders who care deeply about what we do and how we do it. We believe in showing up with empathy, iterating constantly, and always putting clinicians first.

Suki is an Equal Opportunity Employer. We’re committed to building a team that reflects the diverse communities we serve — and to creating a culture of inclusion, belonging, and bold ambition.

The Details

In compliance with the State of California Pay Transparency Law, the base salary range for this role is between $210,000 - $225,000 in CA.  This range is not inclusive of any discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

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