ML Infra Engineer

As a Sensor & Material Characterization Lead, you'll bridge the gap between real and synthetic, working directly with customers and engineers to understand and model their sensing systems — and the materials those sensors observe. You will combine technical expertise with strong communication skills, hands-on time with hardware, and work directly with our software product. You won't be starting cold: you'll ramp up working directly alongside the current lead.

Responsibilities

• Own the data infrastructure and tooling behind our machine learning workflows: indexing, batch pipelines, freshness, quality assurance, and analytics

• Ensure high throughput and clean APIs for the distributed training cluster.

• Take new data systems from zero to one: scope them, build them, and run them in production. For example, metadata, cataloguing and search systems.

• Maintain high-quality, balanced, and representative datasets by supporting and/or driving data science and analytics

• Integrate and normalize heterogeneous data sources from vendors and bespoke collection hardware with varying modalities. e.g. text, images, video, point clouds, and 3d geometry.

Qualifications

• Technical hardware knowledge across all three main sensor modalities: cameras, lidars, and radars.

• Hands-on laboratory experience building, working with, and debugging custom laboratory equipment and sensing hardware.

• Experience working with non-visible systems (SW/LW IR, UV, Radar).

• Experience with computer graphics rendering.

• Understanding of related material properties such as optical BRDF, permittivity, etc.

• Basic metrology skills for sensors and materials — for example, spectral material reflectance, radar antenna/lobe pattern measurement, or camera lens MTF.

• Ability to read, interpret, and apply technical standards (e.g. EMVA-1288 or comparable sensor and measurement standards).

• Understanding of sim-to-real gap problems and their impact on model validity.

• Previous autonomy experience — self-driving vehicles, drones, aircraft, or industrial/assembly robots.

• Familiarity with signal processing for these sensing systems (e.g. camera ISPs, radar/lidar DSPs).

• Foundational knowledge of engineering principles for sensing systems, such as optical and RF engineering.

• Proven ability to work effectively with incomplete information and make sound technical decisions.

• Proficiency in Python scripting for data analysis, testing, and automation.

• Excellent technical communication skills, with the ability to translate complex concepts for various audiences.

• Experience organizing work streams, removing team obstacles, and negotiating shared resource usage.

Ideally you also have:

• Practical experience with optical imaging, photonics, and RF system engineering.

• Experience with material optical measurement instrumentation (spectrophotometers, goniometers, integrating spheres).

• Experience developing custom measurement or calibration hardware/software.

• Knowledge of OpenCV and computer vision principles.

• Experience with optical design software (Zemax, CodeV, or similar for chosen sensor).

• Familiarity with relevant standards, such as EMVA-1288 for camera characterization.

• Rust programming experience.