Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
San Francisco Office · Remote · New York Office · San Francisco, California, United States
Open 5 months, first seen by us 155 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Machine LearningFrom the employer’s posting
We're looking for a rare individual who thrives at the intersection of cutting-edge deep learning architectures and high-performance computing.
While we prefer candidates willing to relocate to San Francisco or New York City, we are willing to consider full-time remote candidates of exceptional talent who are willing to travel frequently to our two office sites.
Profile and optimize existing PyTorch and JAX code without hurting model accuracy
Write CUDA, Triton, or Warp code to speed up performance-critical sections
Work with NVIDIA on tooling and represent Achira's needs to them
Work day-to-day with scientists to find the highest-impact areas
We're looking for a rare individual who thrives at the intersection of cutting-edge deep learning architectures and high-performance computing. You will help shape the future of molecular machine learning by engineering high-efficiency implementations of advanced architectures for foundation simulation models, accelerating simulations to the limits of the hardware while maintaining fidelity to the underlying physics.
While we prefer candidates willing to relocate to San Francisco or New York City, we are willing to consider full-time remote candidates of exceptional talent who are willing to travel frequently to our two office sites. Travel is part of all roles at Achira, both to conferences and corporate on-site activities.
Take existing PyTorch and JAX, profile and optimize it without compromising model accuracy
Develop with frameworks like CUDA, Triton, Warp, etc. to accelerate performance critical code sections.
Liaise with NVIDIA to represent our needs and implement their tooling in our environment.
Work day-to-day with scientists to identify areas of greatest impact
Engineer with at least two years professional experience in GPU optimization
Deep understanding of GPU programming fundamentals.
Solid track record of observable artifacts (e.g., GitHub) showing optimization work.
Experience collaborating on software projects across multi-person teams.
Open 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,418 similar postings that came down. Coming down is not always a hire.
5 open jobs
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
What You’ll Do - Take existing PyTorch and JAX, profile and optimize it without compromising model accuracy, reproducibility, and robustness with respect to scientific objectives. - Develop with frameworks like CUDA, Triton, Warp, etc. to accelerate performance critical code sections.
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
At Achira, we are building a team of world-class scientists, ML researchers, and engineers to work together to move beyond the beaten path in drug discovery. We are actively exploring the next frontier of model architectures for AI x Chemistry: developing world models for the physical microcosm. Our goal is to make biology at the molecular level something that can be learned, predicted, and designed.
At Achira, you’ll operate at the frontier scale of massive compute, massive data, and massive ambition. You’ll own impactful work end-to-end, from ideation to architecture to deployment on distributed infrastructure. We are a well-funded, talent-dense organization that values rigor, speed, execution, and an ownership mindset. We’re looking for new members who share our sense of relentless urgency and are natural collaborators who value team success.
We're looking for a rare individual who thrives at the intersection of cutting-edge deep learning architectures and high-performance computing. You will help shape the future of molecular machine learning by engineering high-efficiency implementations of advanced architectures for foundation simulation models, accelerating simulations to the limits of the hardware while maintaining fidelity to the underlying physics.
While we prefer candidates willing to relocate to San Francisco or New York City, we are willing to consider full-time remote candidates of exceptional talent who are willing to travel frequently to our two office sites. Travel is part of all roles at Achira, both to conferences and corporate on-site activities.
Take existing PyTorch and JAX, profile and optimize it without compromising model accuracy, reproducibility, and robustness with respect to scientific objectives.
Develop with frameworks like CUDA, Triton, Warp, etc. to accelerate performance critical code sections.
Liaise with NVIDIA to represent our needs and implement their tooling in our environment.
Work day-to-day with scientists to identify areas of greatest impact, including travel to our SF and NY working groups to collaborate.
Engineer with at least two years professional experience in GPU optimization.
Deep understanding of GPU programming fundamentals.
Solid track record of observable artifacts (e.g., GitHub) showing optimization work.
Experience collaborating on software projects across multi-person teams.
Even if you hit none of these bonus features, we encourage you to apply!
Experience working with multi-cloud distributed compute systems.
Experience working with multi-site distributed company team.
Experience working with equivariant architectures that operate on 3-D point clouds.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
San Francisco, California, United States
We're looking for a rare individual who thrives at the intersection of cutting-edge deep learning architectures and high-performance computing. You will help shape the future of molecular machine learning by engineering high-efficiency implementations of advanced architectures for foundation simulation models, accelerating simulations to the limits of the hardware while maintaining fidelity to the underlying physics. While we prefer candidates willing to relocate to San Francisco or New York City, we are willing to consider full-time remote candidates of exceptional talent who are willing to travel frequently to our two office sites. Travel is part of all roles at Achira, both to conferences and corporate on-site activities. What You’ll Do
No clear work-authorization passage found. Eligibility is unconfirmed.