Optimize large-scale AI training and inference workloads for throughput, latency, and cost. Responsibilities include GPU kernel optimization, distributed systems tuning, memory and parallelism optimization, profiling across CPU/GPU systems, model compression, production LLM inference optimization, and data-driven performance measurement. The role also involves cross-functional collaboration, code and design reviews, mentoring engineers, and shipping reliable production systems.
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
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected]. Learn more about Bright Vision Technologies
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: 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.
- 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.
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected]. Learn more about Bright Vision Technologies
Bright Vision Technologies is an Equal Opportunity Employer.
Similar Jobs
Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
Implements operational excellence and continuous improvement programs, trains and coaches employees on CI tools, facilitates process improvement, validates benefits, establishes standards, and benchmarks external best practices. The role requires strong facilitation, communication, change management, logical thinking, influence, and results orientation, with experience in TPM, Lean Six Sigma, or comparable continuous improvement leadership.
Top Skills:
Continuous ImprovementLean Six SigmaTotal Productive Maintenance (Tpm)
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Conduct on-site and desktop risk assessments for conventional and renewable power facilities and construction projects. Translate technical findings into underwriting decisions, recommend loss mitigation strategies, support claims analysis, maintain risk files, and advise underwriters, claims teams, and clients. The role also involves account ownership, technical reporting, business development, professional development, and regular travel.
Top Skills:
Microsoft Office Suite
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Manage complex environmental and commercial casualty claims from initial loss through resolution. Responsibilities include coverage analysis, liability assessment, reserving, litigation strategy, settlement negotiation, payment oversight, and directing defense and coverage counsel. The role also partners with underwriting and reinsurance teams, monitors environmental liability developments, mentors claims staff, and advises leadership on emerging exposures and claims practices.
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
