Staff Machine Learning Engineer Computer Vision & Multi-Modal AI

The opportunity
We are building the next generation of AI-driven game experiences generative world models neural rendering and multi-modal understanding that turn images text and 3D primitives into interactive worlds. As our Staff Machine Learning Engineer you will be a core technical leader bringing state-of-the-art computer vision and multi-modal models transformers diffusion networks vision-language models (VLMs) and JEPA-style architectures from research into robust production-grade systems.

This is a deeply hands-on high-impact role. You will help define the modeling anddeployment strategy drive architectural decisions across the ML stack and mentor a teamof senior and mid-level engineers. Your work will directly shape the quality capability andperformance of AI features experienced by billions of players across cloud server andon-device targets.

What youll be doing

Technical Leadership

• Help set the technical vision and roadmap for computer vision and multi-modal AI models spanning transformers diffusion models vision-language models and JEPA-style generative architectures.
• Drive design and implementation of models for image and video understanding generation segmentation detection and dense prediction as well as multi-modal reasoning over images text and 3D inputs.
• Make sound decisions on model architecture training strategy data pipelines and evaluation balancing quality capability latency and cost across deployment targets.
• Own the path from research prototype to production: training fine-tuning distillation export and serving with deployment spanning cloud GPUs through to efficient on-device inference where the product requires it.

Architecture & Research Translation

• Collaborate directly with research scientists to translate novel CV and multi-modal model architectures into deployable well-engineered implementations.
• Design scalable systems for multi-modal inference that process diverse inputs images
• video text primitives and metadata and produce rich outputs from semantic
• predictions to pixel-level generation.
• Track and rapidly adopt breakthroughs across the field: vision-language pretraining and
• alignment efficient diffusion (e.g. consistency models flow matching) efficient attention
• e.g. FlashAttention linear-attention variants) and tokenization/representation learning
• for vision.
• Where latency or device constraints demand it apply compression quantization pruning and knowledge distillation and work with appropriate runtimes (e.g. TensorRT ONNX Runtime CoreML TFLite) to meet performance budgets.
• Team & Cross-Functional Leadership
• Lead and mentor a team of ML engineers; define engineering best practices code review standards and rigorous benchmarking and evaluation methodology.
• Partner with research platform engineers product managers and runtime teams to align ML capabilities with product roadmaps and target-platform constraints.
• Champion a culture of measurement: define KPIs for model quality accuracy latency memory and cost and ensure the team tracks them rigorously.

What were looking for

• 6 years in ML engineering with significant depth in computer vision and/or multi-modal modeling.
• Proven production experience with transformer-based and diffusion-based vision models (e.g. ViT CLIP/SigLIP-style encoders Stable Diffusion DETR/SAM-style architectures)
• Strong command of the full model lifecycle: data curation training and fine-tuning evaluation and serving at scale.
• Familiarity with efficient attention diffusion samplers multi-modal fusion and vision-language alignment techniques.
• Strong Python and modern deep-learning tooling (PyTorch); solid software
• engineering fundamentals.
• Track record of technical leadership: setting direction influencing cross-functional partners and growing engineers.

You might also have

• Experience with world-model video-generation or neural rendering pipelines (NeRF
• 3DGS or similar).
• Experience deploying models to constrained or on-device targets including quantization
• INT8/INT4/FP16) pruning distillation and runtimes such as CoreML TFLite ONNX
• Familiarity with mobile SoC accelerators (Apple Neural Engine Qualcomm Hexagon/AdrenoARM Mali) or compiler stacks such as MLIR TVM or XLA.
• Contributions to open-source ML frameworks or peer-reviewed CV/ML research publications.
• Background in real-time graphics or game engine pipelines (Metal Vulkan OpenGL ES).

Additional information

• Relocation support is not available for this position
• Work visa/immigration sponsorship is not available for this position

Benefits
At Unity we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility specific offerings and coverage vary based on the country and employment status.

While specific benefits vary here are some of the ways we strive to take care of our eligible team members globally: 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

Life at Unity
Unity NYSE: U is the worlds leading game engine powering play for more than 3 billion consumers each month. The top mobile games in the world the most played PC indie titles the most innovative console games and virtually all of the top XR and Web Games are developed deployed and grown in Unity. Unity also enables teams across industries like automotive manufacturing and healthcare to design simulate and collaborate in 3D closing the gap between ideas and reality. For more information please visit .

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive innovative environment and celebrate our employees across age race color ancestry national origin religion disability sex gender identity or expression sexual orientation or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers partners and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience please fill out this form to let us know.

Pursuant to the San Francisco Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

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