AI Researcher / Machine Learning Engineer
Quick facts
- Pay
- $175,000 - $300,000 a year
- Type
- Full-time
- Location
- San Francisco, California
- Background
- PhD
- Experience
- 1–6 years
- Skills
- Python, Machine Learning
- Industry
- Information Technology — 666 open jobs
- Visa in listing
- H-1B, OPT
- Apply
- Free to apply — never pay anyone for a job offer or visa sponsorship
Job description
Job Title: AI Researcher / Machine Learning Engineer
About This Role
We are looking for a dedicated AI Researcher to join our team for our client. Unlike some positions that focus strictly on applied vision engineering and explicitly state they are not research roles, this role bridges the gap between frontier applied AI and real-world execution. Inspired by frontier applied AI labs building zero-touch enterprise solutions, you will help define our roadmap and engineering bar while working on high-leverage projects. You will be responsible for taking ML systems from concept to real-world scale.
Key Responsibilities
- Design the agentic layer.
- Implement self-checking, reflection, and verification passes before results reach humans or downstream systems.
- Build systems that measure model performance across every new store, catch when results stop meeting standards, and refine the models.
- Orchestrate agentic workflows and retrieval augmented generation.
- Productionize prompt pipelines, retrieval, and light fine-tuning, where it moves the needle.
- Stand up inference paths with low latency serving and token-level observability.
- Own vision tooling and testing infrastructure, and try out new model variants on the edge device and in the cloud.
Minimum Requirements
- 1-6 years of experience as a software or machine learning engineer.
- Has taken a CV or ML system from concept to real-world deployment, including evals, training pipelines and signal refinement.
- Experience in tech stacks including Python and Elixir.
- A top-decile AI power user who keeps exploring new tools.
- Ownership mentality, crisp communication, and comfortable making decisions with 80 percent information.
- Move fast without breaking things, not afraid to learn new stacks, bring a we will figure it out attitude.
Preferred Qualifications
- Master's in Computer Science.
- PhD in Computer Science, Physics, Applied Mathematics, Artificial Intelligence, or a related field.
- Familiarity with LangGraph is a plus.
- Open-source work or side projects are a big plus.
Compensation and Benefits
Base salary range of $175K-$300K, with total comp including equity. Alternative compensation packages may offer $185K-$205K along with competitive equity. Top-tier health benefits and flexible PTO.
Logistics Work Policy Location: We offer flexible options based on the project team, ranging from in-person 5 days a week at the San Francisco office to fully remote within the United States. Remote Requirements: For remote roles, you must be US-based, working at least 5 hours of overlap with Mountain Time, with one on-site per quarter.
Visa Sponsorship: Depending on the specific role, we may be open to visa transfers (e.g. OPT, H1B transfers) and sponsorships (e.g. new H1B, TN), or the role may require a US citizen or green card holder.
Visa sponsorship record
No public sponsorship records foundWe didn't find H-1B, H-1B1, E-3 or green card (PERM) filings under the name Vivo HealthStaff in the Department of Labor and USCIS data. That doesn't mean the job can't be sponsored — the company may file under a different legal name, be new to sponsorship, or sponsor a visa that isn't in these datasets (for example H-2B or J-1).
Tip: ask the recruiter early, in writing, which visa they sponsor and whether they cover the legal and filing fees.
Which visas can work for this job
Occupation: Data Scientists (SOC 15-2051) — estimated from the job title.
- Mentioned in the listing
H-1B, OPT
- H-1B cap-exempt employer
Regular cap-subject employer — a new H-1B needs to win the lottery in March (unless you already hold cap-counted H-1B status).
- TN (citizens of Canada and Mexico)
This kind of role may fit the USMCA profession “Mathematician / Statistician” — it depends on the actual duties. No lottery, no cap; you need the matching degree or license.
- E-3 (Australia) and H-1B1 (Chile, Singapore)
Same degree requirement as H-1B, but no lottery and a separate quota that is rarely filled.
- O-1 (extraordinary ability)
For candidates with awards, publications, press, a high salary or critical roles at distinguished organizations. No cap, no lottery; the employer files a petition.
- STEM OPT extension (F-1 students)
Requires an E-Verify employer. We didn't find this company in the E-Verify list — ask HR.
Salary vs prevailing wage
Level III (experienced)Data Scientists · San Francisco-Oakland-Fremont, CA. Annual prevailing wages set by the Department of Labor (OFLC).
| Level | Prevailing wage | H-1B lottery odds* |
|---|---|---|
| Level I | $110,386 | ~15% |
| Level II | $142,438 | ~31% |
| Level III | $174,512 | ~46% |
| Level IV | $206,565 | ~61% |
This job pays $175,000–$300,000 a year — that's Level III (experienced). In the wage-weighted H-1B lottery a Level III registration gets 3 entries; estimated selection chance about 46% — better than average.
* Odds are DHS projections for the FY2027 wage-weighted lottery (actual results vary by year and employer). Since the FY2027 cap season the H-1B lottery is weighted by wage level: Level I = 1 entry, II = 2, III = 3, IV = 4. The level is set by the offered wage against the prevailing wage for the occupation and worksite. Separately, a $100,000 fee for new H-1B petitions for workers outside the US was announced in 2025; as of September 2026 a federal court ruling keeps it unenforceable while appeals continue — check the current status.
Sources: U.S. Department of Labor OFLC disclosure data (H-1B/H-1B1/E-3 LCA, PERM), OFLC prevailing wage data, USCIS H-1B Employer Data Hub, E-Verify participating employers. Data loaded: LCA FY2024–FY2026, PERM, USCIS Data Hub, OFLC wages; updated 2026-10-03. Employers are matched by name, so records of companies with similar names can occasionally be mixed up. This is general information, not legal advice — talk to an immigration attorney about your case.