- Own research problems end to end: framing, data, experiments, ablations, and the model that ships
- Advance deep learning models for object detection, semantic segmentation, and structured extraction on vector and raster construction drawings
- Build multimodal systems combining visual layout, geometry, and text
- Design evaluation frameworks to continuously improve the model
- Stay current with computer vision and ML research and evaluate what's relevant to construction-industry problems
- 2–8 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
- Depth 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
- Experience training and evaluating neural networks at scale, and at least one model you've taken to production
- Strong Python and PyTorch, across the modeling, training loop and the data pipeline
- Practical GPU and distributed training experience
- Judgment about data: what to label, what to synthesize, what to discard
- The ability to read current research critically and say what's worth trying
- Master's or PhD in Computer Science, Machine Learning, Electrical Engineering, Mathematics, or a related field
- Familiarity with vector graphics and CAD formats (SVG, DXF, DWG, IFC)
- LLM and NLP experience like structured extraction, retrieval over long documents
- Model optimization: quantization, pruning, knowledge distillation
- Publications or open-source contributions in computer vision or deep learning
- Experience with cloud environments (GCP, AWS, or Azure)
- Empirical over theoretical — we'd rather run the experiment than argue about it
- Truth-seeking, including about our own results. A negative result reported early is worth more than a positive one defended late
- Research is judged by whether it holds up in front of 1,200 contractors, not by whether it's clever
- Honest feedback, given directly
Skills Required
- 2-8 years of applied machine learning or AI research experience focused on computer vision and deep learning
- Depth in object detection, image segmentation, image processing, OCR and layout analysis, self-supervised or representation learning, or multimodal and vision-language models
- Experience training and evaluating neural networks at scale
- At least one machine learning model taken to production
- Strong Python and PyTorch skills across modeling, training loops, and data pipelines
- Practical GPU and distributed training experience
- Strong judgment about data labeling, synthesis, and filtering
- Ability to critically evaluate current machine learning research
- Master's or PhD in Computer Science, Machine Learning, Electrical Engineering, Mathematics, or a related field
- Familiarity with vector graphics and CAD formats including SVG, DXF, DWG, or IFC
- LLM and NLP experience, including structured extraction or retrieval over long documents
- Experience with model optimization such as quantization, pruning, or knowledge distillation
- Publications or open-source contributions in computer vision or deep learning
- Experience with cloud environments such as GCP, AWS, or Azure
What We Do
Attentive.ai is the #1 landscape management software provider with end-to-end automation for all field services businesses across the landscaping, asphalt and paving, facilities maintenance, and snow removal industry. Our software- powered by cutting-edge Artificial Intelligence (AI), is designed to optimize your workflows and help you scale effortlessly. Our property measurement software, Automeasure, caters to landscaping maintenance and construction, paving maintenance and construction, facilities maintenance, and snow removal businesses. Automate your takeoffs on up-to-date aerial imagery and blueprints, helping sales teams save time, bid more, and win more. Our landscape management software, Accelerate, arms you with a truly end-to-end solution for all commercial landscape maintenance and construction jobs through automated workflows. Over 500 businesses across the field services industry—landscaping, snow management, paving maintenance, construction, and facilities maintenance industries in the US and Canada trust Attentive.ai to drive their revenue. This includes the most successful sales teams, like those at U.S. Lawns, Juniper Landscaping, Maldonado Nursery & Landscaping, United Land Services, Elements Mountain Company, Beary Landscaping, Paved Assets, East Coast Facilities, BrightView, Case Snow, and LandCare. Backed by marquee investors, including Sequoia Surge and InfoEdge Ventures, we are building to solve the biggest challenges facing the outdoor services businesses.
