AI Performance Engineer
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AI Performance Engineer
75,000–100,000 / Year
Location
Remote
Experience
Senior
Posted
Jul 30, 2026
Apply by
August 29, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Home
Job Description
AI Performance 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: AI Performance Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $75,000–$100,000 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 an AI Performance 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 [\[email protected\]](/cdn-cgi/l/email-protection). Learn more about Bright Vision Technologies
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.
Key Responsibilities
- Extract maximum throughput and minimize latency across training and inference workloads.
- Reduce cost across large neural network systems.
- Perform low-level kernel optimization and distributed system tuning.
- Work with cross-functional partners to translate requirements into engineered solutions.
- Conduct code reviews, design reviews, and mentor junior engineers.
Requirements
- Bachelor's or Master's degree in Computer Science
- Computer Engineering
- or a related field
Skills Required
PythonC++Deep Learning Workload OptimizationDistributed TrainingDistributed InferenceProfiling ToolsModel CompressionMemory HierarchiesParallelism StrategiesGPU ArchitectureCommunicationCollaborationAnalytical ReasoningMeasurementDebuggingLLM Inference OptimizationvLLMTensorRT-LLMDeepSpeedTritonCUTLASSFinOps
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