{"id":2581039,"url":"https://alion.io/job/plusai-senior-machine-learning-engineer-perception","title":"Senior Machine Learning Engineer, Perception","company":{"id":22363,"name":"PlusAI","domain":"plus.ai","url":"https://alion.io/company/plus","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"C","score":67,"open_postings":40,"ghost_share":0.55,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-08-04T17:01:00Z","employer_posted_date":"2026-08-04","last_verified_at":"2026-10-15T13:06:12Z","board_verified":true,"closed_at":null,"days_open":71,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":71},"description":"We are seeking a highly skilled Machine Learning Engineer with deep expertise in developing Bird’s Eye View (BEV) fusion models using multimodal sensor inputs, particularly LiDAR. You will play a central role in designing scalable perception algorithms that integrate data from camera, LiDAR, and radar sensors to support autonomous driving and 3D scene understanding.\nResponsibilities\nDesign, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs.\nBenchmark perception models using large-scale datasets and well-defined quantitative metrics.\nCollaborate cross-functionally with research, data, and deployment engineers to refine models and support real-world applications.\nMaintain a strong focus on performance, robustness, and scalability for deployment in production systems.\nEnsure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.\nEnsure team compliance with QMS, monitor quality, and drive process improvements.\nRequired Skills:\nPh.D. or Masters in AI, Computer Science, Electrical Engineering, Robotics, or a related field.\nPh.D. new grad or Masters + 3 years industry experience\nProficiency in Python and experience building deep learning pipelines.\nStrong expertise in PyTorch, TensorFlow, or JAX.\nProven experience with LiDAR-based 3D perception and BEV representation models\nDeep understanding of multimodal sensor fusion architectures and techniques.\nFamiliarity with camera, LiDAR, and radar modalities and their synchronization, calibration, and integration in perception pipelines.\nSolid foundation in computer vision, deep learning, and 3D geometry.\nPreferred Skills:\nIndustry or academic experience in autonomous vehicle perception, robotics, or related areas.\nHands-on experience developing deep learning models in real-world or production environments.\nExperience with distributed training, high-performance computing, or GPU 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