{"id":189088,"url":"https://alion.io/job/centific-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":9945,"name":"Centific","domain":"centific.com","url":"https://alion.io/company/centific","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"C","score":62,"open_postings":95,"ghost_share":0.632,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Redmond, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Digital Twin","optional":false},{"name":"Embodied AI","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"JAX","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NVIDIA NeMo","optional":false},{"name":"Physical AI","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"RAPIDS","optional":false},{"name":"TensorFlow","optional":false},{"name":"Tool Use","optional":false},{"name":"Triton","optional":false},{"name":"Vertex AI","optional":false},{"name":"World Models","optional":false},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"Isaac Sim","optional":true},{"name":"Kubernetes","optional":true},{"name":"MLFlow","optional":true},{"name":"Ray","optional":true},{"name":"Sensor Fusion","optional":true},{"name":"TensorRT","optional":true},{"name":"Weights & Biases","optional":true}],"status":"live","first_seen_at":"2026-09-01T00:00:00Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-18T05:49:41Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":47},"description":"About Centific\nCentific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem-comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets-to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.\nOur mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.\nAbout Job\nAI Engineer - Vision AI, Agentic Systems & Physical AI\nLocation: Seattle / Palo Alto / Remote\nJob Description\nCentific’sPhysical AI team is building next-generation AI systems at the intersection ofVision AI, multimodal foundation models, agentic AI, simulation, and real-world robotics. We work on practical and frontier problems spanning video understanding, autonomous systems, embodied intelligence, data pipelines, evaluation, and deployment.\nWe are looking for anAI Engineer who can bridge research and production: someone who can build, fine-tune, evaluate, and deploy AI systems across vision, language, video, simulation, and agentic workflows. You will work closely with research, data science, and platform engineering teams to turn advanced AI ideas into scalable, customer-ready systems.\nThis role is ideal for an engineer with strong hands-on experience in modern AI/ML systems, a solid grasp of multimodal and agentic architectures, and an interest in Physical AI challenges such asperception, dexterity, navigation, simulation, and autonomous decision-making.\nKey Responsibilities\nDesign, build, and deploy AI/ML systems acrossVision AI, multimodal AI, agentic AI, and Physical AI use cases.\n\nDevelop and integrate models forvideo understanding, imageperception, tracking, multimodal reasoning, autonomous workflows, and robotics-related tasks.\n\nWork with research and engineering teams toproductionizemodels using platforms such asNVIDIA NeMo, Riva, RAPIDS, Triton, Isaac stack, AWS Bedrock, GCP Vertex AI, and related SDKs.\n\nBuild pipelines forlarge-scale structured and unstructured data, including video, audio, sensor, and text data.\n\nImplement andoptimizemodel inference, evaluation, monitoring, drift detection, and governance workflows in production environments.\n\nSupport experimentation withLLMs, VLMs, world models, agent frameworks, tool-using agents, and memory-enabled agentic systems.\n\nContribute to AI systems forsimulation, digital twins, roboticsperception, dexterous manipulation, long-horizon task execution, autonomous driving, and edge-case evaluation.\n\nPerform data analysis, error analysis, benchmarking, and model improvement for robustness, safety, and generalization.\n\nCollaborate directly with customers and internal teams toidentifyrelevant datasets, define success metrics, and translate business needs into AI system design.\n\nHelp build reusable internal frameworks, accelerators, and data products for multimodal and agentic AI deployments.\n\nQualifications\nMaster’s degree inComputerScience, MachineLearning, or equivalent practical experience.\n\n5+ years of experience building and deploying large scale AI/ML systems in production.\n\nStrong programming skills inPython and solid experience with modern ML frameworks such asPyTorch, TensorFlow, or JAX.\n\nHands-on experience withVision AI, including one or more of: image/video models, object detection, tracking, segmentation, grounding, video analytics, 3D vision, or multimodal perception.\n\nExperience withGenerative AI, includingLLMs, VLMs, multimodal pipelines, RAG, agents, or agent orchestration frameworks.\n\nFamiliarity withagentic AI concepts such as tool use, planning, workflow orchestration, and memory; experience withagentic memory or knowledge-graph-backed agents is a plus.\n\nExperience working with NVIDIA AI ecosystem tools such asNeMo, RAPIDS, Riva, Triton, andideallyexposure toIsaac Sim / Omniverse or related simulation environments.\n\nExperience building scalable inference or training pipelines onGPU infrastructure, with familiarity in performance optimization, distributed systems, or high-performance networking.\n\nAbility to design experiments, evaluate hypotheses, and implement optimization workflows for real-world AI systems.\n\nStrong communicationskills and ability to work directly with customers, researchers, and cross-functional engineering teams.\n\nPreferred Qualifications\nExperience withrobotics, autonomous driving, simulation, digital twins, or embodied AI systems.\n\nFamiliarity withRay, Kubernetes, Docker,FastAPI, TensorRT, MLflow/W&B, or related MLOps and distributed AI tooling.\n\nExposure tosensor fusion, audio/video analytics, multimodal data pipelines, orroboticsdata formats.\n\nExperience with model governance, observability, safety evaluation, or production model monitoring.\n\nComfort working across both applied engineering and research-driven prototyping.\n\nWhy Join Us\nWork on frontier problems inVision AI, agentic AI, and Physical AI.\n\nBuild systems that connectresearch-grade models to real deployments.\n\nCollaborate with a strong cross-functional team spanning engineering, data science, simulation, and robotics.\n\nHelp shape the next generation of AI systems for real-world action.\n\nSalary: $160,000-$220,000 + OTB\nCentific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. 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