Solutions Engineer
Ultralytics is hiring a Solutions Engineer for a remote role open to applicants in United States. Level rates it ; you can apply on Ultralytics.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting lists this role as remote.
- Tools and skills the posting cites include OpenAI, Anthropic and PyTorch.
- Level classifies it as a senior role.
- Level lists 14 other open roles at Ultralytics.
AI in this role
Solutions Engineer needed to design computer vision architectures, build YOLO prototypes, and guide customers through AI model deployment.
About Ultralytics:
At Ultralytics, we commit to relentless innovation in the AI space and seek team members who resonate with our ambition to produce the world's best YOLO AI models. If you're obsessed with AI, eager to make an impact on the world, and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team.
🌍 Join the team powering the future of vision AI
Hello, hola, 你好, こんにちは, नमस्ते, hallo, bonjour! Thanks for stopping by — we know your time is valuable, so here's what makes Ultralytics special.
⚡ Who we are
At Ultralytics, we're on a mission to simplify AI for everyone. As the creators of the world's leading Ultralytics YOLO models, we empower millions of developers, researchers, and companies worldwide to build state-of-the-art computer vision applications.
Following our $30M Series A round, we're expanding rapidly across our global hubs. This is an opportunity to join a fast-scaling, high-performance team that's redefining the future of vision AI — where ambition meets impact, and ideas become reality.
We move fast. We build boldly. We execute with purpose. And we do it together.
💼 About the role
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.
🚀 What you'll do
Technical discovery and solution design
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.
Prototyping and deployment
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.
Customer engagement and enablement
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.
Ecosystem contribution
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.
📈 What success looks like
3 months: Ramped on the YOLO stack and customers, co-running discovery, and delivering your first demos and project kickoffs.
6 months: Owning technical discovery and POCs end to end, unblocking live deals or at-risk accounts, and earning trust from the AEs and CSMs you support.
9 months: Converting technical evaluations into wins or saves, shipping reusable assets, and providing actionable feedback to the wider organization.
12 months: Becoming the technical partner AEs and CSMs want on their biggest accounts, with POCs that convert and referenceable customer deployments.
🧠 Skills and experience
Core 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 have
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.
🌟 Why this role
Real impact: Your solutions will power vision AI in production across systems used by millions of devices.
Demand you don't have to manufacture: YOLO is the world's most popular computer vision model, and customers already come to us looking to do more with it.
Build at the source: Work directly on top of the YOLO ecosystem with clear lines to Product and Engineering.
A team that ships: Join a fast-moving, high-standard team that values results over routine.
Customer ownership: Stay involved beyond the demo and see your technical work reach production.
🚫 What this isn't
This isn't a slideware Solutions Engineer role. You won't hand off after the demo or hide behind a deck — you'll build the solution, get it deployed, and own the technical outcome throughout the client lifecycle.
🌟 Cultural fit
At Ultralytics, we set bold goals and execute with speed, precision, and teamwork. We're driven by hard work, ambition, and resilience — building fast, learning constantly, and delivering measurable impact.
You'll thrive here if you:
Take ownership and deliver results with focus and accountability.
Combine strategic thinking with hands-on execution.
Value excellence, grit, and creativity in equal measure.
See collaboration as the foundation for meaningful progress.
💰 Compensation and benefits
We reward excellence and impact — not just tenure or title.
Competitive compensation: Competitive compensation packages
On-site collaboration: Work with passionate builders in one of our global hubs (NYC).
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.
👉 Check out Ultralytics careers and our office locations to learn more about our culture, values, and teams.
🌎 Where and how you can work
We believe great work happens where passion meets purpose.
This is a full-time, on-site role based in New York.
Applicants must have legal authorization to work in the country of application.
You will report to the Head of Customer Success and Implementation.
What we offer:
Cutting-Edge, Next-Generation AI Computer Vision Technology: Contribute to building cutting-edge computer vision AI models based on the YOLO framework.
Impactful Work: Shape the future of AI-powered solutions that transform industries.
Collaborative Culture: Join a talented and passionate team that values open communication and innovation.
Ultralytics Handbook
Comprehensive guide to our company's mission, vision, values, and operational practices. This handbook is designed to provide key insights and resources for our (future) team members, collaborators, and community to align with Ultralytics' core principles.
Link: https://handbook.ultralytics.com/
Ultralytics is an equal opportunity employer committed to building an inclusive workplace. We believe that everyone should be able to bring their whole selves to work, and we do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or any other legally protected status.
How we rate this
Solutions Engineer at Ultralytics rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where solutions architecture was part of your work. What did you do?
- Tell me about a project where model deployment was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, Computer vision, Machine learning, Solutions Architecture, and Model Deployment. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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