As a Research Engineer, you will translate research concepts into efficient code, build reusable components, and optimize model performance. You will work on cutting-edge technology and operate at the intersection of artificial intelligence and next-generation computing. This role offers the opportunity to work on highly complex problems and enable breakthroughs.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Kadence is partnered with an exciting and innovative Quantum AI company in the Bay Area, working with cutting-edge technology and operating at the intersection of artificial intelligence and next-generation computing.
The Role
As a Research Engineer, you will act as a bridge between theoretical research and real-world implementation. You’ll partner with scientists and researchers to translate early-stage ideas into scalable, high-performance systems.
Your work will focus on building the tools, infrastructure, and optimized implementations that enable rapid experimentation and accelerate the pace of innovation across the team.
Location:
San Francisco Bay Area
Key Responsibilities
Research & Algorithm Enablement
- Translate research concepts and algorithms into efficient, production-quality code
- Build reusable components and libraries to support ongoing research efforts
- Develop frameworks that allow rapid prototyping and iteration of new ideas
- Contribute to benchmarking and evaluation methodologies for experimental approaches
Machine Learning Systems
- Design and implement training pipelines for advanced and hybrid ML models
- Optimize model performance across training and inference workflows
- Apply numerical methods and optimization techniques to support model development
- Enable reproducible experimentation with strong tracking and data management practices
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Performance & Systems Engineering
- Develop high-performance computing solutions, particularly leveraging GPUs
- Improve efficiency, scalability, and reliability of compute-intensive workloads
- Support distributed systems and large-scale experimentation environments
- Build tools that connect high-level algorithms to underlying execution systems
What We’re Looking For
- Experience building shared infrastructure, frameworks, or tools used by technical teams
- Strong ability to interpret research papers and implement them effectively
- Solid understanding of performance optimization in compute-heavy systems
- Practical approach to software engineering, including testing and iteration
- Curiosity and interest in emerging areas of AI and advanced computing
Preferred Experience
- Proficiency with PyTorch, JAX, or similar ML frameworks
- Experience with GPU programming (e.g., CUDA or equivalent)
- Background in numerical computing, optimization, or scientific computing
- Familiarity with large-scale ML systems or research environments
- Strong foundation in mathematics (linear algebra, probability, algorithms)
- Exposure to compilers, low-level systems, or performance-critical infrastructure is a plus
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Why Join
This role offers the opportunity to work on highly complex, forward-looking problems that push the boundaries of AI and computing. You’ll play a key role in enabling breakthroughs by turning ideas into systems that scale.
What’s Offered
- Competitive salary and equity package
- Comprehensive health and wellness benefits
- Flexible PTO and supportive work culture
- Visa sponsorship available where applicable
- Collaborative, mission-driven team environment
Comp
- $200,000 - $240,000 base, plus equity and benefits
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