{"id":4090907,"url":"https://alion.io/job/valeo-principal-ai-engineer","title":"Principal AI Engineer","company":{"id":4446,"name":"Valeo","domain":"valeo.com","url":"https://alion.io/company/valeo","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":76,"open_postings":295,"ghost_share":0,"stale_share":0.963,"repost_share":0,"time_to_fill_p50_days":33,"computed_at":"2026-11-11T05:49:22Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tuam, Ireland"],"countries":["IE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CARLA","optional":false},{"name":"Edge AI","optional":false},{"name":"Embodied AI","optional":false},{"name":"Gaussian Splatting","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Interpretability","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Transformers","optional":false},{"name":"Vision-Language-Action","optional":false}],"status":"live","first_seen_at":"2026-11-05T00:00:00Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-12T00:08:37Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Valeo is a tech global company, designing breakthrough solutions to reinvent the mobility. We are an automotive supplier partner to automakers and new mobility actors worldwide. Our vision? Invent a greener and more secured mobility, thanks to solutions focusing on intuitive driving and reducing CO2 emissions. We are leader on our businesses, and recognized as one of the largest global innovative companies.\nValeo anSWer Product Line\nValeo anSWer Product Line is a world leader in providing advanced driver-assistance (ADAS) and automated driving/parking systems. The AI Platform team is responsible for developing custom-built, state-of-the-art neural architectures designed to leverage the full power of today's most advanced multi-core automotive embedded platforms and Neural Processing Units (NPUs). Moving beyond traditional modular perception pipelines, the team applies state-of-the-art End-to-End (E2E) deep learning, imitation learning, and reinforcement learning to directly map multi-modal sensor inputs to vehicle control and trajectory planning. We specialize in redefining the state-of-the-art in AI, leveraging large-scale data and foundational driving models to deliver next-generation, fully differentiable automated driving systems for leading global OEMs.\nPosition Overview\nAs a Principal AI Engineer, you will be responsible for the architectural design of end-to-end deep learning solutions enabling the next generation of automated driving and parking platforms. Working as part of a multidisciplinary team, you will utilize deep domain knowledge to technically guide the development of holistic, sensor-to-action AI models. You will be responsible for the design of state-of-the-art E2E algorithms, leveraging substantial driving datasets, behavioral cloning, and closed-loop simulation. You will be expected to remain at the absolute forefront of technological developments in the rapidly expanding fields of large driving models, embodied AI, Vision-Language-Action (VLA) models, and edge compute optimization.\nResponsibilities\nArchitect E2E Driving Models: Lead research and design for fully differentiable, sensor-to-control neural networks powering automated driving and parking.\nDirect AI Governance & Alignment: Chair the AI Technical Steering Committee to approve designs, unify network backbones, and guide legacy algorithm migration.\nGuide Hardware-Software Co-Design: Partner with embedded engineering teams to inform SoC partitioning, pipelining, and AI optimization strategies (quantization, pruning, memory bandwidth) for multi-core ARM, DSP, and dedicated NPU hardware. \nDeliver RFI/RFQ Technical Architectures: Spearhead novel AI system proposals for pre-development programs and commercial vehicle bids.\nSupport Safety & Regulatory Compliance: Collaborate with systems and safety engineering to align E2E architectures with automotive safety standards (e.g., ISO 21448 SOTIF) and AI regulations, advising on model interpretability and safety boundaries. \nDrive Research & Intellectual Property: Lead university research partnerships and generate invention disclosure memos to secure strategic patents.\nRequired Skills/Experience\nRelevant BSc, BEng, or PhD (Mathematics, Physics, Computer Science, or Engineering) with 7+ years of applied experience in deep learning and autonomous systems.\nDeep understanding of modern machine learning architectures (Vision Transformers, Sequence-to-Sequence models, BEV networks, and Vision-Language-Action models).\nAlgorithm development experience in end-to-end autonomous driving, imitation learning, reinforcement learning, or advanced trajectory planning.\nExtensive experience with edge AI hardware, heterogeneous SOCs, and Neural Processing Units (NPUs) for deploying large-scale models.\nProficiency in deploying AI models to embedded platforms.\nExperience with large-scale ML data pipelines, auto-labeling, and driving data curation.\nProven track record in the automotive, robotics, or autonomous vehicle industry.\nExcellent English language communication skills, both written and verbal.\nHigh level of innovation, motivation, and technical leadership.\nAcademic publications and/or active IP/patents in the fields of deep learning, automated driving, or robotics.\nDesired Attributes\nExperience with closed-loop autonomous driving simulators (e.g., CARLA, internally developed simulation engines) and neural simulators (e.g., NeRFs, 3D Gaussian Splatting for driving).\nDeep understanding of modern ML frameworks (PyTorch 2.x) and MLOps pipelines for continuous training of E2E models.\nJob:\nEngineering DisciplinesOrganization:\nPlatform ClusterSchedule:\nFull timeEmployee Status:\nRegularJob Type:\nPermanent contractJob Posting Date:\n2026-07-31Join Us !\nBeing part of our team, you will join:\n- one of the largest global innovative companies, with more than 20,000 engineers working in Research & Development\n- a multi-cultural environment that values diversity and international collaboration\n- more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth\n- a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development\nMore information on Valeo: https://www.valeo.com","description_format":"text","description_chars":5328,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate 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