This one is closed
Live roles like this one
- D 4h ago
- B 23h ago
-
F
1d ago
Charly 60-100k EUR
-
C
1d ago
Prior Labs | Berlin, Freiburg, NYC | ONSITE | Full-time | Technical PM, ML Infra, Research
Prior Labs ONSITE
See every "ML Systems Engineer" role →
Get new “ML Systems Engineer” roles by email
One email a day with what is new in "ML Systems Engineer". Nothing new, no email.
We confirm the address first, and every mail carries an unsubscribe link. Alerts are ours, not a third party's.
Why this grade
This listing scored 79/100, which is a B. It lost the most ground on remote clarity.
- Pay transparency 25 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Mid level Contractor
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: MLOps Engineer (JAX, PyTorch, Pallas/Triton)
Type:Contract
Compensation:$70–$110/hour
Location:Remote
Commitment:40 hours/week
Role Responsibilities
- Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics.
- Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to MLOps and ML systems problems.
- Evaluate MLOps tasks and solutions and provide clear, written technical feedback.
- Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks.
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
Qualifications
Must-Have
- 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization.
- Hands-on production experience with JAX and/or PyTorch at scale.
- Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton.
- Demonstrable career progression.
- Ability to engage reliably for at least 40 hours/week during weekdays.
- Strong written communication skills and the ability to explain complex technical decisions clearly.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check:
- For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
Quick question · anonymous · one tap
Would you apply to this job?
Answer to see what other job seekers said.
Your turn · no account needed
Help the next applicant
You may know something about this listing that we cannot see from here. One tap. No account needed. Signed-in reports earn points once the evidence agrees with you.
I know what it pays
Sign in with Google to earn points for reports — 100 confirmed points buy a week of Early Access.
Where this listing came from
- 02 Oct 2026 Himalayas first sighting
Seen on 1 board over 0 days.