Engineer

About the job

We’re a stealth robotics startup in Palo Alto hiring an engineer to define and ship a canonical Tactile Tensor and the reference SDK + conformance suite that makes tactile data reproducible, interoperable, and directly usable for robotics perception and foundation-model training. Critical requirement : deterministic, byte-stable serialization + strict versioning, plus tokenization-ready interface ... s (tensors → stable token streams) for Transformer-style robotics pipelines—without heavy dependencies. What you’ll do • Define the Tactile Tensor : units, coordinate frames, timestamps, shapes, uncertainty, required metadata, and forward / backward compatibility rules. • Build a lightweight reference SDK (Python and / or C++) that validates, serializes / deserializes, and produces identical outputs across platforms. • Specify training-grade data contracts : deterministic windowing / patching, normalization / quantization, and token schemas that are stable across sensors and logging setups. • Ship a public-facing spec + examples + CI conformance tests so external robotics labs / OEMs can implement against it with confidence. • Architect the tensor representation to ensure physical invariances (e.g., coordinate-frame independence, scale-invariant contact patches) so that policies trained on one robot's geometry generalize to another. Requirements • PhD in a relevant field (Robotics, Computer Science, Applied Mathematics, Electrical Engineering, or similar), or 3+ years of equivalent industry experience. • Excellent software engineering fundamentals (API design, packaging, CI, testing, docs). • Python and / or C++ proficiency (both ideal). • Proven ability to design deterministic serialization and conformance tests (identical inputs → identical bytes across platforms). • Experience with high-rate numeric data formats (Arrow / Parquet / Zarr / Protobuf / FlatBuffers or similar). • Ability to design metadata + lineage for robotics datasets (device ID, calibration artifact ID, robot / config versions, provenance). • Familiarity with ML data pipelines; ability to define tokenization / embedding conventions for transformer training without bundling full ML stacks. • Experience designing data schemas that explicitly handle and flag physical sensor artifacts (saturation, dropout, thermal drift, and variable sampling rates) without crashing downstream model inference. Preferred • Experience authoring standards / specs, file formats, or widely-used SDKs. • HPC / embedded / performance background; strong “minimal dependency” philosophy. • Experience with data integrity / attestation (hashing / signing, provenance chains) for tamper-evident robotics logs. Key Deliverables • PDF Spec : Tactile Tensor schema, metadata / lineage rules, determinism + versioning / migration, conformance criteria. • Reference SDK : lightweight schema objects, validators, deterministic serializer / deserializer, minimal dependencies. • Dataset Container Spec : reproducible storage + examples (streaming + offline parity; robotics log friendly). • ML Interfaces : modular tokenization hooks + reference tokenization recipes (windowing / patching + quantization conventions). • CI Suite : golden files, byte-stability, backward / forward compatibility tests, reference implementations. Contract-to-hire with a clear path to full-time and founding equity for the right fit.

Requirements

• Python
• C++
• Robotics
• Software Engineering
• Deterministic Serialization

Qualifications

• PhD in a relevant field (Robotics, Computer Science, Applied Mathematics, Electrical Engineering, or similar) or 3+ years of equivalent industry experience

Preferred Technologies

• Python
• C++
• Robotics
• Software Engineering
• Deterministic Serialization

About the company

We’re a stealth robotics startup in Palo Alto hiring engineers to define and ship advanced robotics solutions.