Machine Learning Engineer

Mach
San Francisco
Workplace: OnsiteFull timeUSD 120,000 - 220,000 annuallyFunction: Data Science & Machine LearningSkills: ["Ownership","Collaboration","Problem-solving","Attention to detail"]

Own and scale the training, data, and edge-inference backbone for an autonomy stack in contested environments. Build ingestion, labeling/QA, dataset versioning, and reproducible training pipelines; stand up distributed multi-GPU training with experiment tracking and CI evaluation. Deploy and optimize real-time models on Jetson-class hardware, generate synthetic data to close sim-to-real gaps, and instrument runtime drift/health to drive redeployment loops.

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FursaFursa
Mach
Mach
2 weeks ago

Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Own and scale the training, data, and edge-inference backbone for an autonomy stack in contested environments. Build ingestion, labeling/QA, dataset versioning, and reproducible training pipelines; stand up distributed multi-GPU training with experiment tracking and CI evaluation. Deploy and optimize real-time models on Jetson-class hardware, generate synthetic data to close sim-to-real gaps, and instrument runtime drift/health to drive redeployment loops.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Evolve training and data infrastructure: ingestion from flight/sim/HITL, curation/mining, labeling/QA, dataset versioning (DVC/Parquet), and reproducible dataset builds.
  • •Build and scale training/evaluation infrastructure including distributed multi-GPU training, experiment tracking, model registry, and CI-based evaluation with regression gates feeding retrain/redeploy loops.
  • •Deploy and optimize models for real-time edge inference on Jetson-class hardware using quantization/pruning and TensorRT/ONNX Runtime; profile to meet latency/throughput/SWaP targets.
  • •Build and improve multi-task models across the portfolio (detection, segmentation, tracking, search, classification/ATR, and multi-sensor fusion) as a hands-on IC.
  • •Generate and manage synthetic data at scale (simulation + domain randomization) and instrument runtime health, drift detection, and metrics to close sim-to-real gaps and redeploy faster.

Pay and Benefits

Salary: USD 120,000 - 220,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionRetirement SavingsPaid LeaveLearning Budget

Key Requirements

  • •Strong generalist software engineering in Python for ML/tooling and production C++ on Linux, with profiling/optimization and rigorous testing discipline.
  • •End-to-end experience building ML data and training pipelines: dataset construction, labeling/QA, augmentation, experiment tracking, and reproducible training.
  • •Hands-on training and fine-tuning in PyTorch across modern detection/segmentation/tracking architectures (CNN/Transformer).
  • •Edge and real-time deployment experience, including model compression (INT8/FP16), runtime optimization (TensorRT/ONNX Runtime), and meeting latency/SWaP constraints on Jetson-class hardware.
  • •Data/MLOps infrastructure experience including SQL/Parquet, dataset/versioning tools, CI-based validation, and scalable multi-GPU training.
Experience:Machine learningData pipelinesMLOpsEmbedded inference
Skills:OwnershipCollaborationProblem-solvingAttention to detail
Languages:English
Tech Stack:PythonC++LinuxPyTorchCNNTransformerJetsonTensorRTONNX RuntimeINT8FP16DVCParquetSQLMulti-GPUCICUDAROS 2NVIDIA JetsonDocker

Eligibility

Nationality:U.S. NationalU.S. citizen

Company Brief

Mach
Designs and manufactures unmanned systems, tactical engines, and decentralized defense manufacturing infrastructure (Forge) to scale production of autonomous aerial systems and related propulsion for U.S. defense customers and partners.
Industry: Defense Manufacturing
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Valuation: USD 250M to 500M
Funding: Series B
Headquarters: Huntington Beach, United States
Founded: 2023
Glassdoor
Glassdoor: 3.9
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