Job summary
Job post source
This job is directly from MatX
Job overview
The Machine Learning Researcher role at MatX focuses on systems-oriented ML research to optimize and train large language models on specialized hardware, contributing to advancing AI efficiency and capability.
Responsibilities and impact
The candidate will train and optimize LLMs for MatX hardware, run quality evaluations, build distributed infrastructure for training and inference, and provide ML perspective advice on hardware architecture.
Compensation and benefits
The position offers a US base salary range of $120,000 to $200,000 plus equity, commuter stipend for nearby employees, 401(k) with matching, health, vision, dental, life, and AD&D insurance.
Experience and skills
Candidates must have a Bachelor’s degree in Computer Science or equivalent, strong software engineering skills, experience with training neural networks especially LLMs, and preferably experience optimizing networks for hardware efficiency.
Work environment and culture
MatX emphasizes diversity, inclusion, and equal employment opportunity, with a collaborative work environment in Mountain View requiring in-office presence three days a week.
Company information
MatX develops vertically integrated AI hardware and software solutions aimed at running the largest ML workloads efficiently to advance AI quality and availability.
Job location and travel
The job is located in Mountain View, California, with a requirement to work onsite Tuesday through Thursday.
Application process
MatX does not accept unsolicited resumes from recruiters or third-party agencies; candidates must be authorized to work in the US and comply with export control laws.
Unique job features
The role involves working on cutting-edge AI hardware-software integration for AGI-scale ML workloads, offering equity and a competitive salary.
Company overview
MatX is a technology company specializing in advanced materials informatics, leveraging artificial intelligence and machine learning to accelerate materials discovery and development for industries such as energy, electronics, and manufacturing. The company generates revenue through software-as-a-service (SaaS) platforms, consulting services, and partnerships with research institutions and industrial clients seeking to optimize materials performance and reduce time-to-market. Founded by experts in computational materials science, MatX has established collaborations with leading universities and Fortune 500 companies, positioning itself as a key player in digital transformation within materials engineering. Candidates should be aware of MatX’s emphasis on interdisciplinary teamwork, innovation, and its mission to bridge the gap between data science and materials research. The company’s rapid growth and focus on cutting-edge solutions make it an attractive workplace for those interested in the intersection of technology and materials science.
How to land this job
Position your resume to highlight your strong foundation in computer science, excellent software engineering skills, and hands-on experience with training and optimizing neural networks, especially large language models (LLMs).
Emphasize any experience or coursework related to distributed infrastructure, hardware-aware optimization of neural networks, and your understanding of hardware constraints like FLOPs, memory bandwidth, and parallel processing, as these align closely with MatX's mission and responsibilities.
Apply through multiple channels including MatX's official careers page and LinkedIn to maximize your chances of visibility and consideration for the Machine Learning Researcher role.
Connect with current employees or researchers in MatX's AI or ML divisions on LinkedIn; use ice breakers such as commenting on recent MatX publications, expressing enthusiasm for their hardware-software integration approach, or asking about their experience working on LLM training optimizations.
Optimize your resume for ATS systems by incorporating specific keywords from the job description such as 'LLM training,' 'neural network optimization,' 'distributed infrastructure,' 'hardware efficiency,' and 'software engineering,' ensuring your resume passes initial automated screenings.
Leverage Jennie Johnson's Power Apply feature to automate tailored applications across platforms, identify and connect with relevant MatX team members on LinkedIn, and optimize your resume for ATS, allowing you to focus more effectively on interview preparation and networking.
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