Applications Engineer, San Francisco

3 нед. назад

СШАHybrid

machine visionopticsgpuaicamera setup

Hands-on machine vision role involving optics, lighting, sensors, and AI inspection for manufacturing applications.

.ai is bringing the cutting edge of AI computer vision to manufacturing, solving inspection problems that were previously not solvable with traditional machine vision. We're a full-stack company: we deploy GPU-powered cameras on production lines, run inference on the edge, and operate a platform that supports large fleets of devices deployed across the world.
We're growing extremely fast. Our customers love the product because it works: high accuracy, fast deployment, and an operator-friendly experience that makes real factory rollouts possible, not just pilots.

This is a hands on machine vision role for someone who wants to get deep, fast. You will split your time between the lab and live customer applications: evaluating a lens, optimizing a camera setup, building a proof of concept, troubleshooting an inspection that has to hold on a production line. The work moves from bench to factory floor in weeks, not quarters, and what you learn in the lab shows up directly in what we deploy.
Lab testing and experimentation: Hands on testing with cameras, lenses, lighting, and other machine vision components.
Vision setup builds: Build and evaluate vision configurations for customer applications and internal projects.
Technical test reports: Run application tests and turn out clear, fast technical reporting others can act on.
Technology evaluation: Assess new components and technologies and call whether they improve our systems.
Customer support in the field: Testing, troubleshooting, deployment, and technical problem solving for local customers.
AI vision workflow: Image collection, labeling, training, and model evaluation on AI based inspection systems.
Team enablement: Build the internal test setups, resources, and documentation the broader Applications team runs on.
Optical and hardware projects: Camera calibration, new optical configurations, and hardware evaluation.

Required
1 to 3+ years in machine vision, computer vision, applications engineering, robotics, automation, manufacturing, or a related field.
Strong hands on grasp of machine vision fundamentals: cameras, lenses, optics, lighting, and image acquisition.
Familiarity with lens types and when to use them, including telecentric lenses.
Working understanding of AI based vision and how it differs from traditional rules based vision.
Familiarity with image labeling, model training, classification, object detection, and segmentation.
Strong troubleshooting instincts and a logical, experimental approach to technical problems.
Comfortable working hands on with hardware and testing approaches independently.
Able to document and communicate technical findings clearly.
Eager to learn new technologies quickly, including industrial automation and PLCs.
Based in San Francisco, working primarily from our office, with occasional travel to customer sites.
Strong Preferences
Experience with industrial machine vision systems in production.
Experience selecting or evaluating cameras, lenses, lighting, or optical components.
Hands on experience with AI or deep learning inspection systems.
Experience building proof of concept systems or running feasibility studies.
Exposure to PLCs, industrial controls, or manufacturing automation.
Experience working directly with manufacturing customers.

Applications Engineer San Francisco, CA · Applications · Full time, in office
Compensation: $80,000 to $110,000 USD base, plus an annual performance bonus of up to 20%. Travel: Up to 50%, typically lower.
Become a genuine machine vision expert: optics, lighting, sensors, and AI inspection, on real parts and real lines.
Own the experiment. You decide how to test it, you write the report, the finding changes the deployment.
Sit at the seam of lab research and customer reality, where most vision engineers only ever see one side.
Work directly with the most demanding manufacturers in the world, with Sales, Product, and Engineering a desk away.
Extreme growth and real-world impact: We're not building demos. We're deploying AI systems on real production lines, at scale.
Talent density: You'll work with world-class engineers and operators across AI, embedded systems, and enterprise deployment.
Front-row seat to the AI manufacturing wave: One of the biggest transformations happening in industry right now.
Ownership: Your work directly changes the trajectory of the company.
Global exposure: You'll work with the most advanced customers and factories in the world.