{"id":3586109,"url":"https://alion.io/job/mobileye-machine-learning-software-engineer","title":"Machine Learning Software Engineer","company":{"id":174,"name":"Mobileye","domain":"mobileye.com","url":"https://alion.io/company/mobileye","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":85,"open_postings":63,"ghost_share":0,"stale_share":0.603,"repost_share":0,"time_to_fill_p50_days":46,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Jerusalem, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false}],"status":"closed","first_seen_at":"2026-09-17T12:29:21Z","employer_posted_date":"2026-09-17","last_verified_at":"2026-11-02T11:28:15Z","board_verified":false,"closed_at":"2026-11-02T11:28:15Z","days_open":45,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":45},"description":"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.\nIn 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.\nThe 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.\nWhat will your job look like:\nYour role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.\nYou will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.\nFinally, 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.\nAll you need is:\nB.Sc. in Computer Science, Software Engineering, or related technical field.\nStrong problem-solving skills and ability to tackle complex, real-world production challenges.\nNice to have:\nProficiency in Python and experience with containerization and orchestration technologies (Docker, Kubernetes).\nHands-on experience with model serving frameworks and inference optimization.\nBackground in distributed 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