Deployment Engineer

🏢 OSARO · 📍 San Francisco or Remote · 💼 hybrid · ⏰ Full-time 💰 $100,000 - $140,000 / yr

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Position Summary & Responsibilities

We are looking for a Deployment Engineer to help us deliver our smart automation solutions into customer hands. OSARO combines its software and advanced machine learning with the services and industry expertise needed to deliver improved sight and skill to existing robot applications, while enabling new applications for the factories and warehouses of the future. Our products endow industrial robots with the level of autonomy needed to perform an extensive variety of pick and place tasks and integrate tightly with our customers’ complex software environments.

As a Deployment Engineer, your focus is on the customer. You will intimately understand OSARO’s technology and the customer’s needs/environment so that we can design and implement the best solution for the customer. You will be involved in all stages of customer development, from generating the best-fit solution, to planning the implementation, to supporting deployments remotely and on-site. You will collaborate with all Engineering teams to learn everything there is to know about the hardware, deep learning, computer vision, motion planning, robotic control, etc. components of our product so that you are able to solve all manner of technical problems that might arise.

We value candidates who are passionate about what they build, feel a strong sense of ownership over their work, and love being continually challenged. You are someone who cares deeply about your team so you are both direct and believe in doing what you say.

🎯 Candidate Preparation Guide For OSARO Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Advanced machine learning for robotic manipulation, computer vision robustness, and bulletproof deployment reliability in chaotic fulfillment centers.

📋 Preparation Priorities (Key Areas to Clarify):

1. Academic focus on simulation performance without acknowledging the reality gap in physical hardware deployment
2. Poor understanding of latency constraints and edge-computing limitations on industrial robot arms
3. Defensiveness when questioned about system recovery after a picking failure

✨ Recommended Role Alignment Hook:

I build robust machine learning and vision stacks that allow robotic systems to reliably pick and pack anything in chaotic warehouse environments.

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