{"id":1086216,"url":"https://alion.io/job/attentive-ai-research-scientist-computer-vision","title":"Research Scientist, Computer Vision","company":{"id":3301,"name":"Attentive.ai","domain":"attentive.ai","url":"https://alion.io/company/attentive-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"B","score":79,"open_postings":15,"ghost_share":0.267,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":71,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":275000,"currency":"USD","period":"year","gross":null,"usd_annual":275000},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Image Segmentation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"OCR","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Self-Supervised Learning","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"LLM","optional":true},{"name":"Model Distillation","optional":true},{"name":"Quantization","optional":true}],"status":"live","first_seen_at":"2026-08-31T06:46:53Z","employer_posted_date":"2026-08-31","last_verified_at":"2026-10-20T02:26:48Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":48},"description":"About Attentive.ai:\nAttentive.ai builds AI for construction and field services. Our takeoff and estimating platform, Beam AI, is used by 1,200+ contractors across the US and Canada and has completed over 500,000 takeoffs. Attentive.ai is transforming the field services and construction industries with our flagship AI solution - Beam AI. Our platform empowers businesses to double their bidding capacity and accelerate growth through automation and intelligent insights. More than 1k+ businesses across the U.S. and Canada already use our products to boost sales velocity and streamline operations. We have raised $30.5M in Series B funding, accelerating our mission to make advanced AI tools accessible, practical, and impactful in the real world. We are proudly Backed by Insight Partners, Peak XV (Surge), InfoEdge, Tenacity and Vertex Ventures.\nAbout the Role\nAs a Research Scientist, you'll advance computer vision, deep learning, and NLP that power automated takeoff and estimation. The core problem is unsolved: a plan set is hundreds of pages drafted to dozens of CAD conventions, where the same primitive is a wall, a hatch pattern, or a leader line depending on context a model has to infer.\nYou'd be an early member of the US research team, which means real influence over the directions we pursue. You'll own research problems end to end and take models to production.\nWhat You'll Do\nOwn research problems end to end: framing, data, experiments, ablations, and the model that ships\nAdvance deep learning models for object detection, semantic segmentation, and structured extraction on vector and raster construction drawings\nBuild multimodal systems combining visual layout, geometry, and text\nDesign evaluation frameworks to continuously improve the model\nStay current with computer vision and ML research and evaluate what's relevant to construction-industry problems\nWhat We're Looking For\n2-8 years of applied machine learning or AI research experience with a strong focus on computer vision and deep learning. We'll calibrate level and compensation to what you've built.\nDepth in at least one of: object detection, image segmentation, image processing, OCR and layout analysis, self-supervised or representation learning, or multimodal / vision-language models\nExperience training and evaluating neural networks at scale, and at least one model you've taken to production\nStrong Python and PyTorch, across the modeling, training loop and the data pipeline\nPractical GPU and distributed training experience\nJudgment about data: what to label, what to synthesize, what to discard\nThe ability to read current research critically and say what's worth trying\nNice to have:\nMaster's or PhD in Computer Science, Machine Learning, Electrical Engineering, Mathematics, or a related field\nFamiliarity with vector graphics and CAD formats (SVG, DXF, DWG, IFC)\n LLM and NLP experience like structured extraction, retrieval over long documents\nModel optimization: quantization, pruning, knowledge distillation\nPublications or open-source contributions in computer vision or deep learning\nExperience with cloud environments (GCP, AWS, or Azure)\nHow We Work\nEmpirical over theoretical - we'd rather run the experiment than argue about it\nTruth-seeking, including about our own results. A negative result reported early is worth more than a positive one defended late\nResearch is judged by whether it holds up in front of 1,200 contractors, not by whether it's clever\nHonest feedback, given directly\nCompensation and Sponsorship\nWe are hiring Research Scientists across multiple levels, with opportunities for candidates ranging from approximately 2-8 years of relevant experience; level and compensation will be aligned with experience, research depth, and impact.\nThe base salary range for this role is $170,000 - $275,000, plus equity. The final offer depends on experience and level. We sponsor visas. 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