At Modular, we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about our culture and careers to understand how we work and what we value.
The GenAI Modeling team implements the latest models on top of Modular’s next generation AI platform, whether it’s public open source models to be showcased on the MAX Builds website, or private models for our enterprise partners and customers.
As a senior modeling engineer, you will use your in-depth understanding of modern deep learning architectures, especially but not limited to LLMs, to implement, test and validate models. You’re also expected to mentor more junior engineers in this task. Not only will your work enrich Modular’s model library, but it will also serve as example code for the MAX developer ecosystem worldwide, and will directly inform and guide the development of our platform. You will develop high-level ML code using APIs such as the Python MAX Graph API, as well as basic kernels using the Mojo programming language. A passion for staying up to date with the latest literature in the field, as well as prior research experience is a plus.
LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home.
What you will do:
- Develop AI models, with a focus on GenAI and LLMs, using the MAX platform's Python APIs
- Research and stay up-to-date on the latest model architectures, such as Llama and DeepSeek
- Implement novel models and architectures based on research papers
- Test and evaluate the inference accuracy of models
- Mentor less experienced engineers on model architectures, implementation details, and effective use of modern APIs like PyTorch
- Collaborate with the MAX Platform team by providing feedback on API design and developer experience
- Work with leads and product managers to estimate and plan the development of new models
What you bring to the table:
- Solid understanding of deep learning architectures and concepts such as transformers, diffusion models, attention, KV cache, and more
- Strong experience with Python, core numerical libraries (like NumPy) and deep learning frameworks (e.g., Pytorch, JAX, Tensorflow).
- Solid Python coding skills
- Good grasp of related mathematical concepts, especially linear algebra
Helpful, but not required:
- Kernel development experience (CUDA, TritonLang, etc.)
- Deep learning research experience
- ML API development experience
- Experience training or deploying deep learning models
- Understanding of performance tradeoffs in modern accelerators
- Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.
- World-class Benefits. In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! Please note that specific benefit packages may vary based on your location.
- Competitive Compensation. We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce.
- Team Building Events. We organize regular team onsites and local meetups in different cities.
Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world.
The estimated base salary range for this role to be performed in the US, regardless of the state, is $198,000.00 - $242,000.00 USD.
The estimated base salary range for this role to be performed in Canada, regardless of the province, is $187,000.00 - $270,000.00 CAD.
The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation.
For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.
Modular is proud to emphasize an equal opportunity, safe environment for people to do their best work. Modular is an affirmative action employer. We are committed to providing equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you require reasonable accommodations to participate in the interview process, please let your recruiter know, and we will work with you to meet your needs in compliance with the ADA.
This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.
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