Solutions Engineer

Ultralytics • New York City, NY

15d • $100,000 - $200,000 • Onsite

About The Position

As a Solutions Engineer, you'll turn complex computer vision problems into production systems built on YOLO. You'll lead technical discovery, design architectures, build benchmarks and proof-of-concepts, and guide customers from their first conversation to deployed models. You'll work across Sales, Customer Success, Product, and Engineering while partnering directly with customers in manufacturing, retail, security, robotics, and beyond. This is a hands-on role for an engineer who enjoys writing Python, training and optimizing models, deploying across cloud and edge, and owning outcomes throughout the customer lifecycle. If you thrive on ambiguous problems, direct customer contact, and turning technical possibilities into measurable results, you'll fit right in.

Requirements

• Strong Python and practical experience with YOLO, OpenCV, PyTorch, and computer vision.
• Experience training, optimizing, evaluating, and deploying machine learning models.
• Comfortable with Docker, Git, REST APIs, Linux, cloud platforms, and edge workflows.
• Experience deploying across Linux, macOS, and Windows environments.
• Proven ability to deliver technical demos, workshops, architecture reviews, and POCs.
• Strong communication skills with both technical and executive audiences.
• Independent ownership, urgency, resilience, and results in a high-performance startup environment.
• Passion for AI, open source, and helping customers achieve real outcomes.

Nice To Haves

• Kubernetes, CUDA, TensorRT, ONNX, Jetson, or other edge accelerators.
• Experience with MLOps, model monitoring, CI/CD, or observability.
• Familiarity with AWS, Azure, GCP, serverless systems, or managed inference platforms.
• Experience integrating OpenAI or Anthropic APIs into customer tools.
• Open-source contributions or experience supporting developer communities.
• Knowledge of Ultralytics YOLO workflows and production computer vision solutions.

Responsibilities

• Own technical discovery, translate customer needs into architectures, and define measurable success criteria.
• Evaluate customer data, recommend models, and design training, inference, and deployment strategies.
• Lead technical qualification and solution design alongside Account Executives and Customer Success Managers.
• Build Python prototypes with YOLO, OpenCV, PyTorch, and Docker.
• Create benchmarks, integrations, and production-ready training and deployment workflows.
• Deploy solutions across Linux, macOS, Windows, cloud, and edge environments.
• Diagnose performance, data quality, inference, and hardware acceleration challenges.
• Use the Ultralytics documentation and YOLO guides to deliver reliable customer outcomes.
• Deliver technical demos, workshops, architecture reviews, and proof-of-concepts that move opportunities forward.
• Explain machine learning clearly to engineers, operators, executives, and other non-technical audiences.
• Build trusted relationships and manage technical stakeholders from evaluation through production.
• Turn customer solutions into reusable examples, deployment guides, integrations, and documentation.
• Share feedback with Product and Engineering to improve the YOLO ecosystem.
• Engage developers through the Ultralytics community and GitHub organization.

Benefits

• Competitive compensation: $100k - $200k OTE, alongside equity
• On-site collaboration: Work with passionate builders in one of our global hubs (NYC/Austin).
• Flexible working hours: We value results over routines.
• Generous time off: 24 vacation days, your birthday off, plus local holidays.
• Tech & tools: Work on cutting-edge AI projects that power millions of devices.
• Gear: Brand-new Apple MacBook Air/Pro, Apple Studio Display, and AirPods Pro 3.
• Learning & development: Dedicated budget for personal and professional growth.
• High impact: Your work will shape the future of vision AI.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed