Post-Training Research Engineer, Baseten
$200-275k
Offers Equity
ML application builder for data scientists
Be an early applicant
ML application builder for data scientists
21-100 employees
Be an early applicant
$200-275k
Offers Equity
21-100 employees
Company mission
To make machine learning accessible to every organisation.
Role
Who you are
- A deep understanding of modern ML techniques and tools for training transformers
- Advanced experience in a tensor/array computation library like PyTorch, TensorFlow, Jax, or similar
- A detailed understanding of transformer training parallelism strategies like data parallelism, sharded data parallelism, tensor parallelism, pipeline parallelism, context parallelism
- The experience and knowledge to profile and improve the performance of a distributed GPU program in PyTorch or a similar library
- The ability to perform roofline analysis on a transformer training setup
- A willingness to dive into messy problems, work with researchers, derive specifications by asking important questions, and execute
- Familiarity with HPC and distributed computing platforms like Slurm, Ray, Kubernetes, and Dask
- Familiarity with cluster networking technology like Infiniband, RoCE, GPUDirect
- Solid fundamentals in operating systems concepts like processes, files, kernel drivers, containerisation, and networking protocols
- A sense of creativity and willingness to ask difficult questions about our approach, assumptions, and tooling choices
What the job involves
- We are looking for an engineer with strong experience in machine learning and solid foundations in maths and computer science to join our growing Post-Training team at Baseten
- Custom models are instrumental to the success of Baseten customers
- By inference volume, the overwhelming majority of traffic at Baseten is to and from models that have been post-trained in some way, whether that be through reinforcement learning, supervised finetuning, a recent technique from the literature, or an in-house research technique from Baseten
- The Post-Training team is responsible for the success of our customers’ post-trained models, and we employ a wide array of techniques to produce models that are more efficient and higher quality than even the biggest closed source models for the customer’s specific needs
- Your role as a research engineer is to build the in-house tooling to support all of this
- We care about training a wide spectrum of different model architectures with a variety of techniques efficiently and at scale
- At times this involves zooming deep into a particular technical topic, but more often if involves working across the stack as a whole - systems-level concepts like Kubernetes, cgroups, storage systems, and networking topologies, as well as PyTorch distributed tensor computation, and GPU kernels
Our take
As with its mathematical namesake, Baseten focuses on simplifying the complex. The San Francisco startup focuses on simplifying the integration of artificial intelligence into businesses. The tools that Baseten built demolish the need for businesses to hire specialised engineers, utilising the huge strides in artificial intelligence that we’ve seen in the last few years without adding workload to businesses.
With serious funding behind it, Baseten has grown its team by three times year-over-year over the last five years, especially across engineering and marketing. Having hired talent from companies such as GitHub, Google, Uber, Amazon, and Palantir, part of Baseten's focus is on helping companies implement the tools that they have at their disposal, a long-overlooked aspect of machine learning that many businesses have been eager to champion, but uncertain on how to actually use.
Simplifying the complex world of artificial intelligence for business is no mean feat but the three founders, who met whilst working as engineers at Gumroad, have a lot of experience in how to navigate this gap in the market.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 6 rounds)
Jan 2026
$300m
LATE VC
Sep 2025
$150m
SERIES D
Total funding: $585m
Company benefits
- Remote-first work environment. The Baseten team is welcome to work from wherever they want; fully remote, in our San Francisco office, or a mix of both. Today, our team (including our founding team) is spread across the United States, Canada, and Armenia. We provide a $1,000 stipend for you to make your home-office comfortable and productive
- Regular in-person team summits. We get together as a team three times a year to plan, workshop, and most importantly, get to know each other better
- Unlimited PTO. We ask that everyone take at least 4 weeks of vacation. And we have a company-wide break between Christmas and New Year's Day
- Full healthcare coverage. Medical, dental and vision insurance for you and your family
- Paid parental leave. 16-weeks fully paid parental leave (adoptive and non-birth parents included) and flexibility with schedules while returning to work
- Company-sponsored 401(k) for you to contribute to
- Learning and development budget. We encourage you to take classes, attend conferences, and invest in your craft and we’ll cover expenses to make it happen
Company HQ
Union Square, San Francisco, CA
Leadership
Tuhin Srivastava
(Co-Founder)Previously Co-Founder at Shape, Machine Learning at Gumroad and Skulpt.
Amir Haghighat
(Co-Founder)Previously Head of Engineering at Gumroad, Software Engineer at Yelp and Engineering Manager at Clover Health.
Phillip Howes
(Co-Founder)Previously Co-Founder at Shape, Machine Learning Engineer at Gumroad and Research Assistant at the University of Sydney.
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