The Role
Designs and operates production-grade model serving platforms for LLMs, vision, and recommendation systems. Responsibilities include optimizing inference performance, GPU utilization, routing, batching, caching, autoscaling, observability, deployment workflows, security controls, and incident response. The role requires distributed systems expertise, high-throughput service experience, and collaboration with ML and product teams to deliver reliable, cost-efficient AI services.
Summary Generated by Built In
MLOps Engineer - Remote
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: MLOps Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience Required: 6+ 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 MLOps Engineer 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.
Key Responsibilities
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected] or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
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: MLOps Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience Required: 6+ 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 MLOps Engineer 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.
Key Responsibilities
- Design and operate model serving platforms supporting diverse workloads including LLMs, vision models, and recommendation systems.
- Optimize inference performance using continuous batching, paged attention, speculative decoding, and request multiplexing.
- Implement multi-tenant routing, rate limiting, and quality-of-service policies across model endpoints.
- Build autoscaling and capacity management systems that balance latency, throughput, and cost.
- Tune GPU utilization, memory management, and KV cache strategies for LLM serving workloads.
- Integrate model serving with API gateways, identity systems, and observability platforms.
- Implement caching, prompt deduplication, and response reuse strategies where appropriate.
- Drive end-to-end observability including latency histograms, queue dynamics, GPU utilization, and error tracking.
- Develop deployment workflows including canary releases, shadow testing, and automated rollback.
- Operate incident response for high-availability AI services and drive durable reliability improvements.
- Collaborate with ML and product teams to support new model releases and capability rollouts.
- Implement security controls including request signing, content filtering, and abuse detection at the serving layer.
- Document operational procedures, performance characteristics, and tuning guidance for internal teams.
- Stay current with AI serving research and translate advances into production capabilities.
- 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 [email protected] or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Skills Required
- 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++
- 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
- 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
- Knowledge of 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
Similar Jobs
.jpeg)
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Bright Vision Technologies is a minority-owned organization founded in July 2020 and based in New Jersey, USA. The company specializes in delivering top-tier staffing and IT consulting services, including custom computer programming and systems design. Additionally, they are a product engineering firm with a flagship AI-powered talent intelligence and enterprise automation platform called Lumina, which helps transform IT into a strategic asset for their valued partners.
