Senior ML Software Engineer
Mobileye is seeking an experienced ML Software Engineer to bridge the gap between cutting-edge machine learning research and robust production deployment.
In this position, you will own the deployment strategy and all production data creation for our ML algorithms end-to-end — setting best practices, defining architectural standards, and leading the technical direction for how our models are served at scale. You will combine deep software engineering expertise with hands-on ML deployment knowledge to tackle large-scale ML challenges and build production systems that are reliable, scalable, and future-proof.
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:
- Own all production data creation end-to-end – designing, building, and evolving the pipelines and infrastructure that power our ML systems in production.
- Solve large-scale ML production challenges by designing and optimizing inference pipelines that operate reliably at massive scale, addressing performance, throughput, and reliability challenges head-on.
- Serve as the primary point of contact between algorithm developers, product, BI, and DevOps – driving execution across multiple stakeholders and ensuring smooth delivery of production solutions.
- Drive architectural decisions, promote engineering best practices, and contribute to maintaining high engineering quality across the deployment stack.
- Develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and building new production capabilities.
All you need is:
- B.Sc. in Computer Science, Software Engineering, or a related technical field.
- 3+ years of experience developing and deploying production-grade software on cloud infrastructure, preferably for ML model deployment.
- Proven ability to take technical ownership and independently drive complex production challenges from design to delivery.
- Experience working cross-functionally and managing priorities across multiple stakeholders and teams.
- Strong Python development skills and familiarity with modern production infrastructure and deployment technologies (Docker, Kubernetes, etc.) – advantage.
