Model Serving Engineer
Bright Vision TechnologiesLast week
- Where you can work from
- Remote — United States onlyUnited States
- Salary
- USD 74K–98K / year
- Job type
- Full-time
- Experience
- Senior
Skills
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Job description
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Model Serving Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $74,000–$98,000 Annually
Experience Required: 7+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking a Model Serving Engineer to design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads. The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped serving systems at scale, and understands the trade-offs between latency, throughput, cost, and quality in ML serving.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science or a related field.
- Six or more years of experience in distributed systems, infrastructure, or ML platform engineering.
- Strong proficiency in Python and a systems language such as Go, Rust, or C++.
- Deep experience operating high-throughput, low-latency services in production.
- Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM.
- Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization.
- Familiarity with Kubernetes, autoscaling, and modern cloud platforms.
- Experience with observability stacks including metrics, tracing, and structured logging.
- Solid grounding in performance engineering and capacity planning.
- Strong communication and incident response skills.
- Open-source contributions to model serving infrastructure.
- Experience with multi-region or globally distributed AI serving.
- Familiarity with model quantization, distillation, and compression techniques.
- Exposure to FinOps for AI workloads and cost-efficient serving design.
- Experience supporting external-facing AI APIs at scale.
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to
more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
Originally posted on Himalayas
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Job availability & source
Still listed on the employer's own board at our last check, 7 days ago
This job was originally posted by the employer or source shown below. We re-check the original listing regularly to keep its availability current, and send you straight to it to apply — we never sit in between.
- Source
- Himalayas
- Posted by the employer
- 14 Oct 2026
- First seen by us
- 14 Oct 2026
- Last checked
- 18 Oct 2026
via Himalayas — view on source
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