ML Infrastructure Engineer, Fauna

Benefits

Parental leave

6 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

6 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Not verified

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Source-linked checked Jun 7, 2026

Salary

$185K-$250K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

87% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

ML Infrastructure Engineer, Fauna New York, New York, USA We are seeking a Machine Learning Engineer to work directly alongside our research scientists to train, evaluate, and deploy the models that make our robots move, perceive, and act in the real world. This is a hands-on ML role: you will train policies, debug convergence, run experiments in simulation, and push models onto hardware - not just build the pipes around them. You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training infrastructure - managing GPU clusters, optimizing distributed training, and shipping models to edge devices - but the core of this role is getting in the loop with scientists and making models work. Key job responsibilities Train and iterate on neural network policies for locomotion, manipulation, navigation, and perception using reinforcement and supervised learning Design and run experiments in simulation (Isaac Lab, MuJoCo, or similar) and transfer results to physical hardware Debug training runs end-to-end: diagnosing convergence failures, reward shaping issues, data quality problems, and sim-to-real gaps Optimize models for deployment on edge hardware (NVIDIA Jetson) with strict latency and memory constraints Build and maintain MLOps infrastructure: experiment tracking, model versioning, evaluation pipelines, and reproducible training workflows About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces.

Read the full description at www.amazon.jobs. FewerJobs shows a preview and links to the original posting.