Engineering foundations - 5+ years production infrastructure; strong Python plus one systems language (Go/Rust/C++)
- Expert Linux, networking, and debugging across the full stack
- Infrastructure-as-code (Terraform/Bicep) and containers, including GPU-enabled runtimes
Cloud & orchestration - Production cloud experience (Azure preferred): IAM, storage, managed compute, cost control
- Kubernetes with GPU workloads: scheduling, autoscaling, quotas
MLOps - Distributed training infrastructure: multi-node GPU, checkpointing, fault recovery
- Experiment tracking, model registry, dataset/artifact versioning
- ML CI/CD with automated evaluation gates and rollback
- Data pipelines for large multimodal datasets (video, tactile, time series)
- Observability: GPU utilization, drift, data quality
Edge deployment - Model optimization for constrained targets: quantization, ONNX, TensorRT
- Deployment to embedded hardware (Jetson or similar) with OTA updates and rollback
- Awareness of latency constraints in closed-loop control
Collaboration - Proven record turning research prototypes into supported production systems
- Mentoring engineers and driving practice adoption across a team
- Clear design docs and runbooks
Job Req Type: Experienced
Required Travel: Yes, 10% of the time
Shift Type: 1st Shift/Days
The expected wage range for a new hire into this position is $144,000 to $198,000.
- Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.
- This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.
- This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.