Hardware Optimization Engineer
San Diego, CA
Full Time Mid-level / Intermediate USD 135K - 165K
Netradyne
Elevate fleet safety with Driver•i AI Fleet Camera System. Reduce incidents, improve compliance, and optimize driving performance. Request demo.Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.
POSITION SUMMARY:
We are looking for an experienced Model Optimization Engineer to join our fast-growing technology team. This role will require you to benchmark internal models and perform optimizations to get performance improvements
ESSENTIAL FUNCTIONS:
In this role, you will:
- Work with State-of-the-Art models such as VLMs, Vision Encoders, and other model architectures to get performance improvements (most likely in the form of throughput or memory)
- Work on Edge related model optimizations considering hardware constraints
- Apply post-training model compression techniques from the latest research papers
- Perform performance optimization of ML training code to extract best performance from available hardware
QUALIFICATIONS:
- Familiarity with the internals of various SOTA vision model architectures]
- Familiarity with SOTA VLMs and an understanding of concepts involved in running inference.
- Some Familiarity with one of the Cloud Providers (AWS, Azure, etc.)
- Excellent programming skills in Python
- Be self-driven and demonstrate the ability to derive results with limited supervision.
- Nice to Have:
- Experience in performance optimization of ML code (both training and inference).
- 2+ years of experience writing performant training and inference code
EDUCATION:
Bachelor's Degree in Computer Science or similar field required
Compensation Package_Perks of being a Netradyne employee:
- Salary + eligibility for yearly bonus
- Company equity
- Company Paid Health Care, Dental, and Vision Coverage for you and most of your dependents
- Generous PTO and Sick Leave
- 401(K) with generous company match
- Disability, Life Insurance and Ancillary Benefits
- And much more!
San Diego Pay Range$135,000—$165,000 USD
We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.
If there is a match between your experiences/skills and the Company's needs, we will contact you directly.
Netradyne is an equal-opportunity employer.
Applicants only - Recruiting agencies do not contact.
Recruitment Fraud Alert!
There has been an increase in fraud that targets job seekers. Scammers may present themselves to job seekers as Netradyne employees or recruiters. Please be aware that Netradyne does not request sensitive personal data from applicants via text/instant message or any unsecured method; does not promise any advance payment for work equipment set-up and does not use recruitment or job-sourcing agencies that charge candidates an advance fee of any kind. Official communication about your application will only come from emails ending in ‘@netradyne.com’ or ‘@us-greenhouse-mail.io’.
Please review and apply to our available job openings at Netradyne.com/company/careers. For more information on avoiding and reporting scams, please visit the Federal Trade Commission's job scams website.
Tags: Architecture AWS Azure Computer Science Computer Vision Machine Learning Python Research
Perks/benefits: 401(k) matching Career development Competitive pay Equity / stock options Health care Insurance Salary bonus
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.