{"id":3927883,"url":"https://alion.io/job/ensense-ai-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":4500707,"name":"Ensense AI","domain":"ensense.ai","url":"https://alion.io/company/ensense-3","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Los Angeles, United States"],"countries":["US"],"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":"Anomaly Detection","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Physical AI","optional":false},{"name":"World Models","optional":false}],"status":"live","first_seen_at":"2026-11-07T18:53:35Z","employer_posted_date":null,"last_verified_at":"2026-11-07T18:53:35Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Ensense AI is seeking a Machine Learning Engineer to build the core intelligence that powers its Physical AI platform. The role designs models, training pipelines, and deployment systems to interpret multimodal signals from the physical world, from experimentation through production.\n\nResponsibilities\nDevelop and deploy machine learning models that interpret multimodal sensor, audio, video, and environmental data\nBuild training pipelines, data processing tools, and evaluation frameworks for large scale spatiotemporal learning\nFine-tune foundational models for perception, understanding, and inference in physical environments\nCollaborate closely with software and hardware teams to integrate models on device and in the cloud\nPrototype and validate new approaches for environmental understanding, anomaly detection, and physical world inference\nDesign systems that ensure reliability, scalability, and high quality data\nHelp define modeling strategy, architecture decisions, and long term research direction\nContribute to a culture of engineering excellence, ownership, and speed\n\nSkills\nM.Sc. or higher in computer science or a closely related field\nDeep understanding of machine learning fundamentals with the ability to innovate at the algorithmic level\nExpertise in signal processing techniques for audio or other sensor data\nStrong proficiency in machine learning frameworks such as Pytorch\n2+ years of SW/ML engineering experience\nExperience building and maintaining data pipelines and training workflows\nAbility to take models from prototype to production deployment\nStrong problem solving and comfort in fast paced environments\nClear and concise communication skills\nFamiliarity with world models and multimodal sensor fusion\nExperience with spatiotemporal modeling\nBackground working with real world data from physical environments such as AVs\nExperience deploying models on resource constrained systems\nPrior startup experience or history as an early technical hire\nHigh impact publications\n\nCompany Overview\nEnsense AI develops a physical AI platform utilising multimodal sensors to transform real-world infrastructure signals into actionable data. It was founded in 2023, and is headquartered in Marina Del Rey, California, USA, with a workforce of 2-10 employees. 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