getSummary
Written in English from the original postingThe role is for a Machine Learning Engineer building production ML inference pipelines and backend systems for large multimedia datasets. Responsibilities include planning retrieval pipelines, deploying LLM and vision-language model applications, and scaling distributed backend services. The position is hybrid in New York City or San Francisco and requires U.S. work authorization.
Job description
About the company
Our client is a government technology company.
The role
Raydar is recruiting for this role on behalf of our client. Build machine learning and backend systems that handle large multimedia datasets, owning work from first design through production release in secure, distributed environments. The role suits an engineer who wants to see projects through from concept to launch.
What you'll do
- Plan how large multimedia datasets move through retrieval pipelines.
- Integrate large language models and vision-language models into production applications.
- Build and deploy distributed backend services and machine learning inference pipelines.
- Take projects from initial concept to production release.
- Explain system designs and trade-offs clearly to technical and non-technical colleagues.
Requirements
What we're looking for
- At least 3 years of experience in backend engineering, with strong Python skills.
- Familiarity with ML operations and common frameworks for web APIs, LLM applications and deep learning.
- Production experience deploying large language models, vision-language models or custom ML inference pipelines.
- Solid knowledge of designing and scaling backend infrastructure.
- Clear technical communication, with the ability to explain systems and trade-offs.
- U.S. work authorization and willingness to undergo an FBI background check.
Benefits
Compensation and benefits
- Base salary: USD 165,000 to 250,000 per year
- Retirement plan with 3% employer contribution
- Health and dental coverage
- Flexible time off
Location and work model
- New York City, NY, United States (preferred) or San Francisco, CA, United States
- Hybrid, in office at least 3 days a week
- Full-time
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