Model Optimization Engineer

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: Model Optimization EngineerLocation: 100% Remote (U.S.)Position Type: Full-time, Direct W2Salary Range: $100,000–$150,000 AnnuallyExperience Required: 6+ yearsSponsorship: 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 Model 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.Key ResponsibilitiesProfile and optimize end-to-end AI training and inference pipelines for throughput, latency, and costIdentify and eliminate bottlenecks across data loading, model compute, communication, and memoryImplement and tune quantization, sparsity, and pruning strategies to reduce model footprint and accelerate inferenceOptimize distributed training using tensor parallelism, pipeline parallelism, FSDP, and ZeRO-style shardingTune attention implementations using FlashAttention, paged attention, and related techniquesImplement KV cache optimization, continuous batching, and speculative decoding for LLM servingDrive compiler-level optimizations using Triton, XLA, TorchInductor, or TVM, working with the broader ML framework community to land improvements that translate into measurable end-to-end performance gainsOptimize data pipelines, sharding strategies, and storage access patterns for high-throughput trainingBuild and maintain rigorous benchmark suites and regression frameworks across workloadsCollaborate with ML and platform engineering teams to embed best practices in standard pipelinesDrive cost-efficiency improvements through model architecture, hardware selection, and scheduling strategiesEvaluate new hardware and software offerings, and advise on adoptionDocument performance tuning playbooks and share findings broadly across engineering teamsStay current with AI systems research and translate advances into production improvementsRequired QualificationsBachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related fieldSix or more years of experience in performance engineering, ML systems, or HPCStrong proficiency in Python and C++Hands-on experience optimizing deep learning workloads on modern GPUsDeep understanding of distributed training and inference techniquesExperience with profiling tools across CPU, GPU, and distributed systemsFamiliarity with model compression techniques and their accuracy implicationsStrong grasp of memory hierarchies, communication primitives, and parallelism strategiesExcellent measurement, debugging, and analytical reasoning skillsStrong communication and collaboration skillsPreferred QualificationsExperience optimizing LLM inference at production scaleContributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projectsFamiliarity with custom kernel authoring in Triton or CUTLASSExperience with FinOps for AI workloadsPublications or talks on AI systems performanceHow To ApplyWould you like to know more about this opportunity? For immediate consideration, please send your resume to Harry@bvteck.com or contact us at (908)676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.Bright Vision Technologies is an Equal Opportunity Employer.Equal Employment Opportunity (EEO) StatementBright 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.Powered by JazzHRM4FIDbvP3X