Our mission is to build the Covariant Brain, a universal AI to give robots the ability to see, reason and act on the world around them. Bringing AI from research in the lab to the infinite variability and constant change of our customer’s real-world operations requires new ideas, approaches and techniques.
Success in the real world requires a team that represents that world: diversity of backgrounds, points of view, and experiences. Our common denominator: ambitious expectations, love of learning, empathy for those around us, and a team-first mindset.
Covariant solutions architects help design automation systems that use robotic arms powered by the Covariant Brain to drive value for our customers. They design comprehensive end to end solutions from individual components like conveyors, sensors, sorters and cameras. The solutions architect starts early in the presales process, showing our technology and capabilities, visiting customer sites to better understand their needs and specific workflow, including helping our sales leaders qualify opportunities or provide technical feedback during contract negotiations. The solution architect should have a deep understanding of our AI capabilities and act as the subject matter expert towards our customer, advising them on what is feasible today and what the future with Covariant will look like. The architect leads our solutions engineering team (mechanical engineers, software developers, project managers, and more) to design and build a successful solution and report back on the market trends in their specific region. They also represent Covariant to the customer, managing the customer relationship, and determining the customer’s needs.
AREAS OF FOCUS
- Customer communication: Help our customers figure out how to get value from the Covariant Brain, and understand the customer’s problem and workflow deeply
- Solution Design: Translate that customer understanding into an automation design, deploying physical components and writing clear specs and requirements for our engineering team
- Curiosity: The role will require you to learn about our technology stack, and how to operate it effectively
- Be a key contributor from day 1 on a small team that’s growing fast
- Push the boundary of possible with a world-class machine learning team
- Design robotic cells that have never been made before, and watch the ideas in your head go from paper to physical reality
- Outstanding big-picture thinking with a strong problem-solving attitude
- Customer-facing experience in a technical role or equivalent communication skill
- Fluency in German language (C1 or higher)
- Bachelor's degree in a technical field (robotics, software, mechanical engineering, physics, etc.) with a Master's or Ph.D. preferred or relevant technical experience
- Proficiency in writing, reading, and understanding code
- Desire to meet with our customers (travel 15-30%)
NICE TO HAVES
- Past experience with warehouse automation systems and/or a presales engineer for an AI software company
- Experience with robotics
- Experience with data analytics and visualization
- Work on complex software integrations
SAMPLE WEEK IN THE LIFE
- Monday - Record a custom demo video of the Covariant robot picking and sorting a customer’s items. On a call with them later, explain the intricacies of which aspects of the process will improve as we add more customer-specific training data to the Brain. Plan next steps with the sales team.
- Tuesday - Review some mechanical designs coming out of our London office for a solution that is expected to be sent at the end of the week. You’ve brainstormed ideas for it last week but seeing the latest iteration you’re worried that a small % of the customers' items won’t flow through the cell as it's been designed. Lead meetings to try to figure out how to solve the problem.
- Wednesday - Travel to South-West Germany to visit the order fulfillment center of a prospect. You want to understand the whole workflow and see how our robot can fit into the bigger picture. Take notes, pictures and videos to help you translate the process you saw into a written use case description document that will serve as the backbone of the solution design. Make sure that the prospect sees you as a technical expert in the field of AI robotics. Travel home.
- Thursday - Write custom code to analyze historical data from the site you visited on the previous day. Extract from the data the relevant metrics to compare manual workflows to robotic picking, the number of robots that could be installed and their expected performance. Build a slide deck to present the results internally and to our customers with convincing and easily understandable data plots.
- Friday - Talk with the lead developer at the software vendor whose software is upstream of our robot at the pilot site. You want to make sure she will be able to modify their communication protocol so that they become robot-suitable. Communicate the changes necessary to the prospect.
COMPANY CORE VALUES
STRIVING FOR EMPATHY
TAKING ON THE IMPOSSIBLE, TOGETHER
- Health, dental, and vision coverage for you and your family
- Unlimited PTO
- Flexible work hours
- 401(k) plan and match (applies only to United States employees)
- Lunch and dinner each day (for on-site employees)
- Monthly Health & Wellness budget
- Quarterly Learning budget
Atcovariant.ai we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products, and our community.Covariant.ai is proud to be an equal-opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
Covariant is a California-based startup that develops artificial intelligence (AI) software for industrial robotics. The company was founded in 2017 by PhDs from UC Berkeley and Stanford University, and it has raised over $100 million in funding from investors like Lux Capital, Baidu Ventures, and Andreessen Horowitz. Covariant's software uses a combination of deep learning, reinforcement learning, and other AI techniques to allow robots to learn