--- title: 'Machine Learning Engineering Team Lead at Treeswift Inc' canonical: 'https://feeny.ai/job/machine-learning-engineering-team-lead-treeswift-inc-new-york-a76kjj5w14e0' type: 'job' last_seen: '2026-11-01' --- # Machine Learning Engineering Team Lead at Treeswift Inc - **Company:** Treeswift Inc - **Location:** New York, NY - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-27 - **Last confirmed live:** 2026-11-01 - **Apply:** https://jobs.ashbyhq.com/treeswift/ec957fe9-0bb1-4445-b702-8e258057bf5b ## Job description About Treeswift: In the face of rising threats, increasing pressure on affordability, and unprecedented demand for power, Treeswift empowers energy companies to modernize their field work to meet the growth and challenges ahead. We build physical AI for the field worker: whether on foot or in a vehicle, our technology is an ironman suit for engineers, linemen, and vegetation crews: same worker, same boots on the ground, now operating at 10x productivity. Our platform is powered by cutting edge hardware, sensors (LiDAR, camera, etc…), AI and software designed to revolutionize work in the toughest environments. Our technology has enabled our customers to reduce wildfire risk, regulatory and outage risk from vegetation, avoid delays and cost overruns in new construction, and accelerate recovery from severe storms. To tackle this challenge, we are bringing together a team of mission-driven experts with deep industry experience in robotics (Penn, Caltech, CMU) and enterprise software development (Palantir, Stripe, Oracle, MongoDB). We have raised funding from leading investors including Penny Pritzker’s Inspired Capital. We are headquartered in midtown Manhattan, with additional offices in San Francisco and Philadelphia. Our growth is only accelerating. We’re looking for deeply curious and highly ambitious people who want to have a real world impact. Come build the future of (field) work with us. ## About the role ML sits at the heart of Treeswift’s product translating complex sensor data into meaningful insights that drive critical decision-making for our customers. As our business grows the importance of this work only grows with it. You will join at a critical inflection point and will lead the charge on the following priorities (amongst others): - Technical Leadership. You will be responsible for continuing to improve the quality and consistency of our models across a growing breadth of operating conditions. As the breadth of models and datasets grows you will thoughtfully introduce feedback loops and ML Ops that accelerate model improvement. You have excellent judgement on what problems require fast experimentation/validation, and where we should be focused on sustainable scalable improvement over a longer period of time. - Edge model development. Working closely with our robotics and embedded teams, you will support growing exploration of model deployment on devices for real-time use cases. - Lead and grow our team (as needed). We have an incredibly talented ML team distributed across our NYC, Philly and SF offices. You will lead the current team, identify gaps and grow the team as needed. - Collaborate closely with our Software, Robotics, Hardware and Product teams to deliver on Treeswift’s vision and business objectives. You will report to our Head of Software Engineering. This is a full-time, hybrid role based out of our Lower Manhattan, NYC office (2-3 days per week in person, currently pinned to Tuesdays and Wednesdays). ## About Machine Learning At Treeswift Machine Learning at Treeswift is the layer that translates sensor data into meaning for our end-users. At a high-level we develop three categories of model that power downstream business decisions. - Classifying a point cloud - distinguishing ground from vegetation from structures etc. - Identifying individual objects within 3D space — poles, equipment, wires, trees, etc. - Describing characteristics of individual objects. This includes everything from tree species and health, detailed wire types, pole information (height, attachments, etc.) etc. Together this information informs critical decision-making for our customers such as: - What vegetation is a risk to utility infrastructure and how severe is that risk? What action is recommended as a result (trim, removal, etc…)? - Is ongoing asset construction deviating from the expected design and if so how? If so, is this an approved deviation or a quality issue that needs to be addressed before a downstream customer or financial impact? Required skills and experience - Early-stage or fast-moving environments where scope and ownership evolve quickly. - Strong familiarity with models built on images, video, lidar, pointclouds, speech, or geospatial data sources. - Building and using cloud-based training and inference pipelines (including orchestration, deployment, and the operational realities of running models at scale). - Willingness to drive architecture and approach across both, bring innovative ideas and rapid execution to new and existing models, and be accountable for the quality and consistency of our models across a growing breadth of operating conditions. - Leading development of our training and inference pipelines. You will lead how we build and evolve these pipelines as well as move us towards on-device inference for time-sensitive use cases. - 3+ years experience in leadership: setting clear direction for a team, driving architecture and design decisions, reviewing others' work, and mentoring individual engineers. - Experience creating, curating, and cleaning training datasets, and building the evaluation and feedback loops that drive model improvement. - Strong programming skills and expertise in deep learning frameworks such as PyTorch, scikit-learn, and TensorFlow. - Excellent communication and collaboration skills. You have the ability to keep a team distributed across three offices (NY, Philly, SF) well-aligned. You will be a strong partner to the product team on how to balance technical trade-offs and product objectives. Nice-to-haves - Experience developing models for and deploying models to run on edge-devices. - Experience with deep learning training frameworks such as MLflow, Lightning, Weights and Biases, or similar. - Experience with semantic mapping, image processing techniques and/or computer vision fundamentals. - Experience with Apache Airflow (especially 3.x) and/or Astronomer. - Experience with one or more of: Sensor Fusion, SLAM, Visual Odometry. - 8+ years of professional experience ## Benefits - Competitive salary and equity package - Comprehensive medical, dental, and vision coverage for you and your eligible dependents - Life insurance and short- and long-term disability coverage - 16 weeks of fully paid parental leave to support all new parents - Flexible, unlimited paid time off - 401(k) retirement savings plan - Free OneMedical membership - Commuter benefits - Snacks, goodies, and team lunches provided twice a week to keep you fueled and connected with your colleagues. The estimated salary range for this position is $225,000 - $265,000 USD. Total compensation for this position is determined by skills, qualifications, relevant work experience, location, and other factors. This salary estimate excludes the value of any potential bonuses; the value of any benefits offered; and the potential future value of any long-term incentives. This information is provided per the New York City Human Rights Law. Please note that the range provided is applicable only to New York City-based applicants. Base compensation may vary if the work location is outside of New York City. Treeswift  is proud to be an equal opportunity employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected status in accordance with applicable law. If you require any accommodations during the recruitment process, whether it be alternate forms of material, accessible meeting rooms, etc., please let us know and we will work with you to meet your needs. ## About Treeswift Inc ## Company Overview - **One-liner**: Treeswift builds physical AI and robotics solutions that augment field crews for utility grid construction, vegetation management, and asset inspection. - **Entity Type**: Private (Series A) - **Headquarters**: Philadelphia, Pennsylvania, United States (also maintains an office in lower Manhattan) - **Founded**: 2020 - **Founders**: Steven Chen (CEO & Co-Founder), Bianca Rahill-Marier (COO & Co-Founder), Michael Shomin (CTO & Co-Founder), Vaibhav Arcot (Co-Founder & Senior Software Engineer) ## Core Business - **Primary industry**: Physical AI / Robotics for Utility Infrastructure & Vegetation Management - **Target customers**: Large electric utilities across the United States (including PG&E and two of the other five largest utilities in the country) - **Mission statement**: Build physical AI that puts people at the center of the work, not on the sidelines — helping the people who build and maintain the physical world get more done. ## Products & Services - **Treeswift Field Data Platform**: A software platform that integrates with utilities’ existing GIS and planning tools. It processes data from backpack and vehicle-mounted sensors (imagery, LiDAR, GPS, voice) to deliver actionable analytics and 360° field context for construction, vegetation management, asset inspections, and disaster response. - **Backpack & Vehicle-Mounted Sensors**: Hardware kits that seamlessly integrate into existing patrols (on foot or by vehicle) to gather high-resolution ground measurements in any environment — from city sidewalks to remote backcountry. - **AI-Powered Analytics Engine**: Computer vision and machine learning tools that translate raw field data into automated measurements, counts, forms, and reports — reducing the manual busywork for highly skilled field crews. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: Total funding of **$21.7M** across multiple rounds; estimated annual revenue of **$2.1M** - **Notable Investors/Partners**: Inspired Capital (Penny Pritzker), Pathbreaker Ventures, Crosslink Capital, TenOneTen Ventures, Contour Venture Partners, National Science Foundation (grant) - **Growth Signals**: - Headcount grew **100% YoY** (from ~11 to 36 employees) - Active job postings up **550% year-over-year** - Works with PG&E and two of the five largest U.S. utilities - Filed 5 patents (topics include forest ecology, forest management, forest modelling) - Expanding into disaster response and black sky (storm/outage) use cases ## Competitive Advantages - **Niche focus on electric grid labor augmentation**: Addresses a critical and growing need as electricity demand surges from data centers and new industry — utilities must build and maintain more infrastructure while managing wildfire, storm, and compliance risks. - **PhD-level robotics & AI team**: Founders and technical leads hold PhDs from University of Pennsylvania, Caltech, and Carnegie Mellon University, with deep expertise in robot perception, machine learning, and autonomous systems. - **Enterprise DNA**: Leadership team includes former product leaders from Palantir Foundry (built the product suite for business users), plus veterans from Stripe, Oracle, and MongoDB. - **Field operations expertise**: Team includes arborists and vegetation management specialists from the National Park Service and USFS, giving them rare domain credibility with utility crews. - **Patented technology**: 5 patents covering autonomous scanning, forest representation, and tracking/monitoring of geographic regions. ## Strategic Focus - **Scaling across the U.S. utility market**: Expanding partnerships with major utilities beyond PG&E to address the nationwide grid modernization challenge. - **Expanding use cases**: Moving from vegetation management into construction monitoring, asset inspection, and disaster response (both proactive “blue sky” and reactive “black sky” scenarios). - **Growing the engineering and field operations teams**: 13 active job openings spanning machine learning, site reliability, hardware operations, recruiting, finance, and deployment. - **Product development**: Continuing to build AI that works in any environment (urban, remote, all weather conditions) and integrates with any system utilities already use. ## Why Work Here - **Mission-driven work**: Tackle critical infrastructure and climate resilience challenges — helping prevent wildfires, improve grid reliability, and keep electricity affordable. - **Cutting-edge technology**: Work on physical AI combining robotics, computer vision, LiDAR, and machine learning in real-world outdoor environments. - **Strong team culture**: Described as “mission-driven experts” with backgrounds in robotics research (Penn, Caltech, CMU) and enterprise software (Palantir, Stripe, Oracle, MongoDB). - **High growth trajectory**: 100% headcount growth YoY, recently closed Series A, and expanding rapidly with 13 open positions. - **Hybrid/office presence**: Headquarters in Philadelphia (3401 Grays Ferry Ave) with an additional office in lower Manhattan; customer-facing team members located near utility partners across the country. - **Diverse team composition**: 36 employees across technical (30%), general management, consulting, product, project management, sales, HR, finance, and operations. - **Notable perks**: Opportunity to work on patented technology with real-world impact; strong alumni network from top tech companies and universities. ## Sources 1. [treeswift.com](https://www.treeswift.com/) 2. [treeswift.com/team](https://treeswift.com/team) 3. [linkedin.com/company/treeswift](https://www.linkedin.com/company/treeswift) 4. [cbinsights.com/company/treeswift](https://www.cbinsights.com/company/treeswift) 5. 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