We are looking for a graphics engineer to join the Lighting team within Unity Graphics. The role involves maintaining existing graphics features in the Scriptable Render Pipeline and participating in building new features, optimizing graphics solutions for many platforms using innovative rendering methodologies.
Compensation
Base Salary Range: We determine the base salary range for this role based on your primary work location: Denmark- 577,300.00 - 721,600.00 DKK annual
Responsibilities
Maintain existing graphics features in our Scriptable Render Pipeline
Participate in building new graphics features
Solve graphics challenges while delivering maintainable and extensible features optimized for many platforms
Work with artist-facing features for rendering: direct lighting, indirect diffuse and specular lighting, ray tracing, shadow mapping
Lead the development of physics-based machine learning models and infrastructure, collaborating with simulation engineers and research scientists to deliver production-grade solutions.
Responsibilities
Work closely with simulation engineers and research scientists
Transform prototype implementations to robust production-grade model implementations, libraries and tooling
Work with multi-GPU/multi-node distributed systems for training and inference
Optimize models and pipelines at all levels
Design and build scalable infrastructure for end-to-end ML applications on cloud
Research, design, develop, and/or test operating systems-level software, compilers, and/or network distribution software for semiconductor operations
Design, develop, troubleshoot and debug software programs for enhancements and new products
Develop software and tools in support of design, infrastructure and technology platforms, including operating systems, compilers, routers, networks, utilities, databases, cloud-based and Internet related tools
Develop, debug, bring-up, and tune performance of new graphics hardware running on operating systems
Architect and drive the AI Software Stack by establishing best practices and optimizing performance from the lowest-level GPU kernels to large-scale distributed systems.
Responsibilities
Architect and drive the AI Software Stack
Optimize performance from lowest-level GPU kernels to large-scale distributed systems
Leverage Large Language Models (LLMs) and agent-based technologies to accelerate the AMD ROCm ecosystem
Accelerate applications such as foundation models and autonomous AI agents
Contribute to the entire co-design lifecycle, influencing future GPU architectures
Build and extend the physics engine that gives every simulated vehicle, aircraft, drone, and robot physically accurate behavior.
Responsibilities
Implement and extend numerical solvers for dynamics simulation, including implicit, semi-implicit, and constraint-based methods (e.g. matrix-free PCG, direct solvers, PBD/XPBD-style projections), that scale to large, contact-rich scenes.
Develop high-fidelity contact and collision handling, including penetration handling, penalty and dual methods, and friction, that holds up at scale.
Read, evaluate, and implement techniques from state-of-the-art simulation research and from other production engines, adapting them for use in our own.
Validate the correctness of new methods you implement, both mathematically and empirically, so the team can stand behind the engine's fidelity.
Diagnose and resolve simulation instabilities (e.g., energy drift, blow ups, conditioning issues) and profile solver performance to find and fix bottlenecks.
Requirements
engineering or related technical degree (e.g., computer science, applied mathematics, physics, mechanical/aerospace engineering)
Nice to have: variational/energy-based formulations of implicit integration
Forward Deployed ML Engineers work at the intersection of deep technical work and direct customer impact, partnering with leading AI companies and foundation model labs to achieve state-of-the-art performance on workloads like LLM serving, model training, and audio pipelines.
Responsibilities
Work hands-on with companies like Suno, Cognition, and Meta to architect and optimize production AI workloads on Modal
Contribute to open-source projects (e.g., SGLang) and publish technical content
Collaborate with Modal’s product and sales teams, contributing to the platform as both an engineer and a product stakeholder
Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work
Conduct technical demos, experiments, and proofs of concept
Requirements
Nice to have: Side projects
Nice to have: open-source contributions
Nice to have: published work in ML or systems performance
Lead and grow infrastructure and validation engineering teams supporting NVIDIA’s Local AI and PC gaming R&D.
Responsibilities
Lead and grow infrastructure and validation engineering teams responsible for CI/CD, test development and automation, regression analysis, failure triage and debugging support, and lab operations, including hardware health, maintenance, and recovery.
Define and drive the team’s technical roadmap, priorities, and delivery commitments across Local AI and PC gaming, balancing long-term infrastructure improvements with day-to-day engineering needs.
Drive the development and deployment of tests and benchmarks that reflect real-world usage, supported by automation for environment setup, test execution, log collection, and results analysis.
Build tools that help reproduce failures and analyze logs and system metrics.
Partner with engineering teams to identify root causes and resolve functional issues and performance bottlenecks across the hardware and software stack.
Requirements
Bachelor's or master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field
Research Fellow/Associate focusing on AI for audio/acoustic transcription and signal processing
Responsibilities
Leading the effort to translate high-level audio algorithms implemented in other audio prototyping software into a high-performance, architecture-specific code.
Working closely with other researchers to design and implement DSP algorithms that meet system-level constraints.
Defining and implementing software architecture for real-time audio systems on prototype hardware containing a multitude of co-processors.
Developing key AI model that is efficient and suited for acoustic/audio transcription and must have deep knowledge on inter-disciplinary domains.
Develop and implement signal processing algorithms with applications to communication transceivers and/or digital signal processing on various Software Defined Radio (SDR) platforms.
Compensation
$110,400.00 - $165,500.00
Responsibilities
Develop and implement signal processing algorithms
Analyze signal processing performance using MATLAB, Python, or similar simulation environments
Prototype real-time communication systems for emulation and proof of concept
Research advanced signal processing, GPS technology and/or re-configurable communication processing
Document work products in briefings and/or technical reports to customers and colleagues
Requirements
Bachelor’s degree or higher in Electrical Engineering, Computer Science, Physics, Mathematics, or related discipline
Senior Research Machine Learning EngineerNewPhysicsX · London, United Kingdom
Software Development EngineerAdvanced Micro Devices, Inc · Austin, US
Physics Simulation Engineer (Dynamics)Zeromatter Technologies Inc · San Francisco, US
Forward Deployed Engineer - MLModal · London, United Kingdom