Mobileye
AI

MLOps Engineer

Mobileye · ירושלים, JM, IL

Actively hiring Posted 5 months ago

Mobileye is looking for a Machine Learning Software Engineer, who will be challenged by bridging the gap between cutting-edge machine learning research and robust production deployment.

In this position, you will combine software engineering expertise with machine learning deployment knowledge, responsible for taking our algorithms and developing robust production solutions that serve them at scale.

The work at Mobileye’s algorithms department is fast-paced and requires staying ahead of the curve with the latest engineering solutions and best practices adopted across the ML community, while staying informed about emerging solutions in both computer vision and NLP domains and understanding the specific problems they address.

What will your job look like:

  • Your role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.
  • You will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.
  • Finally, you will need to learn and implement new deployment technologies and best practices that can address emerging production challenges as they arise, while staying current with the latest MLOps and inference optimization techniques.

All you need is:

  • B.Sc. in Computer Science, Software Engineering, or related technical field.
  • 2+ years of experience in production software development, preferably in ML deployment.
  • Strong problem-solving skills and ability to tackle complex, real-world production challenges.
  • Proficiency in Python and experience with containerization and orchestration technologies (Docker, Kubernetes)- advantage.
  • Hands-on experience with model serving frameworks and inference optimization- advantage.
  • Background in distributed systems and cloud infrastructure- advantage.

Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Machine Learning Nlp Computer Vision Mlops Ai
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.