AI Optimization Engineer

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 an AI Optimization Engineer to focus on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems. The role spans the full stack from low-level kernel optimization to distributed system tuning, requiring deep understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization.

The ideal candidate has demonstrated impact on production AI workloads, with strong instrumentation and measurement discipline that enables rigorous, data-driven optimization decisions. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers.

The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.

Six or more years of experience in performance engineering, ML systems, or HPC.

Strong proficiency in Python and C++.

Hands-on experience optimizing deep learning workloads on modern GPUs.

Deep understanding of distributed training and inference techniques.

Experience with profiling tools across CPU, GPU, and distributed systems.

Familiarity with model compression techniques and their accuracy implications.

Strong grasp of memory hierarchies, communication primitives, and parallelism strategies.

Excellent measurement, debugging, and analytical reasoning skills.

Strong communication and collaboration skills.

Preferred Qualifications

Experience optimizing LLM inference at production scale.

Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.

Familiarity with custom kernel authoring in Triton or CUTLASS.

Experience with FinOps for AI workloads.

Publications or talks on AI systems performance.

How to Apply

Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected] 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.