Staff Machine Learning Engineer

🕒 July 16

🏄 California – Remote

🏄 California – Remote

💵 $218.4k - $283.9k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 35%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Unity

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2005

🏭 Manufacturing

💼 Consulting

📣 Marketing

Manufacturing • Consulting • Marketing

Unity is a leading platform providing tools and services for creators to build games, apps, and immersive experiences. With high-quality graphics, multi-platform support, and AI enhancements, Unity empowers developers in video gaming and other industries like manufacturing. Unity offers services such as Unity Engine, Unity Cloud, and Unity Grow, which include real-time 3D creation, user acquisition, and game monetization. The company also provides extensive resources, community support, and professional training for creators at all levels. Through its success plans and developer resources, Unity aids in solving complex problems and bringing ideas to life for gaming and enterprise professionals.

📋 Description

• Own the optimization pipeline for the models you ship: model export, graph transformation, operator fusion, memory-layout planning, and hardware-specific tuning across NPU, mobile GPU, and desktop/laptop GPU. • Apply quantization (INT4/INT8/FP16), weight sharing, structured/unstructured pruning, and knowledge distillation to hit hard latency, memory, and power budgets — and validate them against quality bars. • Do low-level performance work: write and tune WebGPU compute shaders (WGSL) and, where relevant, native kernels (Metal, Vulkan/SPIR-V compute, CUDA); profile with browser and platform tools (Chrome/Dawn GPU traces, PIX, Instruments/Metal System Trace, Snapdragon Profiler, Nsight, RenderDoc), and eliminate bottlenecks at the op and memory-bandwidth level. • Apply efficiency techniques — dynamic resolution, token reduction, cross-frame caching/reuse, reduced-step diffusion samplers — as engineering levers to meet budgets on target SKUs. • Work with WebGPU-targeted inference runtimes (ONNX Runtime Web, Transformers.js, WebLLM, TensorFlow.js) alongside native options (CoreML, ONNX Runtime, TFLite, ExecuTorch), and extend or build glue code where off-the-shelf options fall short of our diffusion and VLM workloads.

🎯 Requirements

• 5+ years in software/ML engineering, with meaningful time focused on on-device / edge inference or real-time, performance-critical systems. • Production deployment of transformer- and/or diffusion-based models (e.g., ViT, Stable Diffusion, CLIP/SigLIP-style encoders) on mobile, desktop, or embedded hardware — shipped, not just prototyped. • Hands-on experience with at least one major inference runtime (ONNX Runtime / ORT Web, CoreML, TFLite, ExecuTorch) and a working understanding of operator fusion, memory layout, and runtime scheduling. • Low-level performance engineering: solid command of at least one GPU/compute API — WebGPU/WGSL, Metal, Vulkan, D3D12, or CUDA — and the profiling tools to go with it. • Working knowledge of model-optimization techniques — quantization (INT4/INT8/FP16), weight sharing, pruning, and distillation — and the judgment to apply them to hit latency and memory budgets. • Understanding of target hardware: mobile SoCs (Apple Neural Engine, Qualcomm Hexagon/Adreno, ARM Mali) and/or desktop/laptop GPUs (Apple Silicon, NVIDIA, AMD, Intel). • Strong Python for export pipelines and training-side tooling; familiarity with the core languages of a browser-native runtime (TypeScript/JavaScript, WGSL) is a plus. • Working fluency with the models you deploy — enough to read an architecture, modify it for deployment, and reason about accuracy trade-offs. • A collaborative working style: clear communication, reliable delivery, and a willingness to support and learn from teammates.

🏖️ Benefits

• Comprehensive health, life, and disability insurance • Commute subsidy • Employee stock ownership • Competitive retirement/pension plans • Generous vacation and personal days • Support for new parents through leave and family-care programs • Office food snacks • Mental Health and Wellbeing programs and support • Employee Resource Groups • Global Employee Assistance Program • Training and development programs • Volunteering and donation matching program

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume