Treeswift builds physical AI for field workers in the energy sector. This full-time, hybrid role leads the Machine Learning team, which translates complex sensor data into insights that drive critical decisions for customers. The role reports to the Head of Software Engineering and is based in the Lower Manhattan, NYC office, with 2-3 days per week in person (currently Tuesdays and Wednesdays). The ML team develops models that classify point clouds, identify objects in 3D space, and describe object characteristics such as tree species and health, wire types, and pole information. The estimated salary range is $225,000 - $265,000 USD and applies to New York City-based applicants; base compensation may vary for work locations outside New York City. Treeswift is an equal opportunity employer.
Responsibilities
Technical leadership: improve the quality and consistency of models across a growing breadth of operating conditions; Introduce feedback loops and ML Ops that accelerate model improvement; Decide which problems require fast experimentation/validation and which require sustainable, scalable improvement over time; Edge model development: work with robotics and embedded teams to support model deployment on devices for real-time use cases; Lead and grow the ML team distributed across NYC, Philadelphia, and San Francisco, identifying gaps and growing the team as needed; Collaborate with Software, Robotics, Hardware, and Product teams to deliver on business objectives; Lead how training and inference pipelines are built and evolved, including moving toward on-device inference for time-sensitive use cases; Classify point clouds, identify individual objects in 3D space, and describe object characteristics to inform customer decisions
Requirements
Early-stage or fast-moving environment experience; Strong familiarity with models built on images, video, lidar, pointclouds, speech, or geospatial data sources; Experience building and using cloud-based training and inference pipelines, including orchestration, deployment, and running models at scale; Willingness to drive architecture and approach, bring innovative ideas and rapid execution, and be accountable for model quality and consistency across operating conditions; Experience leading development of training and inference pipelines; 3+ years of experience in leadership, setting direction, driving architecture and design decisions, reviewing others' work, and mentoring engineers; Experience creating, curating, and cleaning training datasets and building evaluation and feedback loops; Strong programming skills and expertise in deep learning frameworks such as PyTorch, scikit-learn, and TensorFlow; Excellent communication and collaboration skills, including keeping a distributed team aligned and balancing technical trade-offs with product objectives
Nice to have
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 employees and eligible dependents; Life insurance and short- and long-term disability coverage; 16 weeks of fully paid parental leave; Flexible, unlimited paid time off; 401(k) retirement savings plan; Free OneMedical membership; Commuter benefits; Snacks, goodies, and team lunches provided twice a week
Stany Zjednoczone · New York
