ML Platform Engineer

Bright Vision Technologies; Monroe (NJ); Remote; USD 100,000 - 160,000; Full time

Job summary

Bright Vision Technologies in the United States is seeking an ML Platform Engineer to design, build, and operate high-performance inference platforms for serving large ML models in production. This role emphasizes systems engineering of AI deployment—request routing, batching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads.

Candidates should have strong distributed systems experience and a track record shipping serving systems at scale, balancing

Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• 10+ years of experience in distributed systems, infrastructure, or ML platform engineering.
• Strong proficiency in Python and systems languages (Go, Rust, or C++).
• Experience with high-throughput, low-latency production services.
• Hands-on experience with LLM inference frameworks (vcLLM, TensorRT-LLM).
• Familiarity with Kubernetes and modern cloud platforms.
• Observability with metrics, tracing, and structured logging.
• Strong communication and incident response skills.

Responsibilities

• Design and operate model serving platforms supporting diverse workloads including LLMs, vision models, and recommendations.
• Optimize inference performance using batching, paged attention, and queueing strategies.
• Implement multi-tenant routing, rate limiting, and QoS across endpoints.
• Build autoscaling and capacity management to balance latency, throughput and cost.
• Tune GPU utilization, memory management, and KV cache strategies for LLMs.
• Integrate serving with API gateways, identity systems, and observability tools.
• Implement caching and response reuse strategies where appropriate.
• Drive end-to-end observability including latency histograms and GPU utilization.
• Develop deployment workflows with canary releases and rollbacks.
• Operate incident response for high-availability AI services and reliability improvements.
• Collaborate with ML and product teams on new model releases.
• Implement security controls and documentation for internal teams.
• Stay current with AI serving research and translate advances into production.

Skills

Python

Go

Rust

C++

Distributed systems

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Kubernetes

TensorRT-LLM

vcLLM

Cloud platforms

Job description

ML Platform Engineer - Remote

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

Job Title

ML Platform Engineer

Location

100% Remote (U.S.)

Position Type

Full-time, Direct W2

Salary Range

$100,000-$160,000 Annually

Experience Required

10+ 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 ML Platform 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

Required Qualifications

• Bachelor's or Master's degree in Computer Science or a related field
• 10 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 vcLLM 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

Preferred Qualifications

• 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

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies is an Equal Opportunity Employer.

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.