Machine Learning Engineer – (ML / NLP) Opportunity

Raydar company

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Machine Learning Engineer – (ML / NLP) in United State

Visa sponsorship 1 day ago

About the Role

We are seeking exceptional ML/NLP engineers to join a fast-growing AI startup tackling fundamental problems in LLM-based code generation, document understanding, context synthesis, and intelligent agents. The ideal candidate will bring a strong background in machine learning or NLP from research or industry experience, coupled with the drive to push innovation forward.


This role is open to a wide range of candidates—from strong new graduates to engineers with up to 10 years of experience—with a sweet spot of 4–6 years.


What You’ll Do

  • Build workflows and agentic pipelines for complex analytical workloads.
  • Design evaluation frameworks and carry out evaluations of a query processing engine.
  • Work closely with customers and founders to shape the product and engineering roadmap.
  • Contribute to defining engineering culture and the company’s evolving tech stack.
  • Collaborate with a team of experts from top tech companies and leading research backgrounds.


What We’re Looking For

  • Strong analytical skills and proven ability to tackle challenging NLP problems.
  • Background in search/retrieval, LLMs, and evaluation pipelines (a plus).
  • Experience in startup or fast-paced environments (highly desirable).
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • A strong signal of excellence (e.g., top academic program, significant ML/NLP experience).
  • 0–10 years of experience as an ML engineer (open to standout new grads).


Compensation & Benefits

  • Salary: $150K – $300K
  • Equity: included in the overall compensation package
  • Visa sponsorship: available for exceptional candidates
  • Work policy: On-site role based in San Mateo


Tech Stack

  • Core: Python, PyTorch (or other ML frameworks)
  • LLM Frameworks: LangChain, Haystack
  • Cloud Platforms: GCP, AWS


Interview Process

  1. Culture Fit (30 minutes)
  2. ML Technical Screen (30 minutes)
  3. Onsite (3–4 hours)


Apply now

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