Design, build, and deploy LLM-powered tools that support software development activities such as code generation, code review, debugging, refactoring, automated test creation, and documentation.
Compensation
The base pay range for this position is $130,000.00-$173,000.00 USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan.
Responsibilities
Design, build, and deploy LLM-powered tools that support software development activities
Develop retrieval-augmented generation (RAG) pipelines that ground model outputs in internal engineering artifacts
Create agentic workflows that interact with engineering toolchains
Evaluate and select models based on performance, cost, latency, licensing, and security requirements
Apply techniques such as prompt engineering, fine-tuning, and parameter-efficient adaptation to improve model usefulness
Requirements
Bachelor’s degree in Computer Science, Software Engineering, or related STEM field
Nice to have: Master’s degree in Computer Science, Machine Learning, or related field
Nice to have: Experience building and deploying LLM-based applications such as RAG systems, AI coding assistants, copilots, or agent-based workflows
Nice to have: Working knowledge of C/C++ and embedded software development environments
Nice to have: Familiarity with fine-tuning, quantization, and efficient inference serving for production-scale LLM systems
Lead inference performance for Runware’s AI Factory, owning kernel development, benchmarking, and team leadership across GPU, HPC, and deep learning systems.
Responsibilities
Own inference performance end to end for the fleet
Set the model performance roadmap
Write and tune CUDA kernels, fuse attention and MLP paths
Build pipelines for new model deployment
Choose and shape the serving stack
Requirements
Nice to have: Diffusion and video generation performance
Lead the architectural strategy, design, and execution of the end-to-end autonomous driving data engine for Bosch XC’s L2+ ADAS and autonomous driving stacks.
Compensation
The U.S. base salary range for this full-time position is $240,000 - $320,000.
Responsibilities
Define and execute the technical roadmap and strategy for the E2E Autonomous Driving Data Engine, including fleet data loop automation, active learning pipelines, auto-labeling, simulation, and MLOps tooling.
Oversee the end-to-end architecture, development, and testing of the AI data flywheel and its seamless interaction with edge fleet triggers, cloud data lakes, model repositories, and automotive target hardware.
Collaborate closely with cross-functional leads (data engineering, cloud infrastructure, embedded runtime SOC teams) to define, drive, and scale the integrated AI machinery ecosystem.
Establish a rapid-evaluation development framework that accelerates the benchmarking, active learning selection, and continuous integration of emerging multimodal E2E AI solutions.
Guide the transition of raw fleet log data and research prototypes into scalable, production-grade training and auto-labeling pipelines, ensuring runtime performance optimization on automotive-grade hardware.
Requirements
Master’s degree or Ph.D. in Computer Science, Robotics, Electrical Engineering, AI, or a closely related field focused on autonomous systems
Senior Software Engineer — ML Inference & Numerics
The role involves making the latest AI models run well on custom silicon, focusing on numerical optimization, LLM inference, and building agentic workflows for model performance.
Locations (4)
Sunnyvale, California, United States
Munich, Bavaria, Germany
North America
Europe
Responsibilities
Build agentic workflows to give agents tools to inspect models, change implementations and numerical settings, run emulation and hardware experiments, and diagnose failures.
Bring up new models quickly and take unfamiliar architectures from reference code to validated, performant execution on accelerators.
Lead end-to-end AI workload optimization strategy, driving performance across AMD’s AI software stack.
Responsibilities
Set the technical vision and roadmap for workload optimization across the AI software stack
Lead the profiling, analysis, and tuning of large-scale models to ensure out-of-the-box performance on AMD hardware
Partner with top customers and hyperscalers to understand unique workload requirements and deliver tailored architectural wins and software optimizations
Collaborate across hardware architecture, compiler, and framework teams to influence future silicon features
Drive the development of advanced tools and frameworks for performance estimation, modeling, and automated reporting
Requirements
PhD or Master’s degree in Computer Science, Electrical Engineering, or related field
Nice to have: High-level technical leadership
Nice to have: AI frameworks (PyTorch, JAX, vLLM, SGLang)
Build, enhance, and support generative AI web applications and backend services.
Compensation
Market competitive salary, commensurate with experience and education.
Responsibilities
Build, enhance, and support production generative AI applications and web-based AI solutions.
Develop Python backend services and AI integrations using Azure OpenAI, Azure AI Foundry, and related Azure services.
Implement RAG pipelines, including document processing, chunking, embeddings, search, context preparation, and source citations.
Implement agent workflows using tool/function calling, structured outputs, conversation context, error handling, execution limits, and human review where needed.
Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools.
Requirements
Bachelor's degree in computer science, engineering, or a related field
Shape the future of AI in Intellectual Property by setting the vision for the Data Science & AI organization and turning advances in machine learning, Generative AI, and Agentic AI into scalable products, smarter operations, and measurable business value.
Compensation
The expected base salary for this position is $240,000–$300,000 USD per year. This role is eligible for bonus earnings. Individual pay is based upon experience, education, skill and ability, expertise, and relevant factors.
Responsibilities
Define and execute the enterprise data science and AI vision, aligning investment and delivery with business strategy, product innovation, and long-term growth.
Differentiate our products, operations, and customer experiences through AI.
Create a multi-year roadmap for machine learning, Generative AI, Agentic AI, and advanced analytics adoption.
Lead the strategy, architecture, and implementation of Generative AI and Agentic AI solutions across the business.
Build scalable AI agents, copilots, assistants, reasoning systems, and workflow automation capabilities.
Set the vision for the Data Science & AI organization and turn advances in machine learning, Generative AI, and Agentic AI into scalable products, smarter operations, and measurable business value.
Compensation
The expected base salary for this position is $240,000–$300,000 USD per year. This role is eligible for bonus earnings.
Responsibilities
Set the vision for the Data Science & AI organization
Turn advances in machine learning, Generative AI, and Agentic AI into scalable products, smarter operations, and measurable business value
Guide a global, multidisciplinary organization from AI strategy to production-grade solutions
Lead enterprise-scale AI teams and bring AI solutions into production
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