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Applied Scientist, Amazon Robotics

Job in Sunnyvale, Dallas County, Texas, 75182, USA
Listing for: Jobverse.io
Full Time position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    Robotics, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
  • Research/Development
    Robotics
Salary/Wage Range or Industry Benchmark: 140000 - 200000 USD Yearly USD 140000.00 200000.00 YEAR
Job Description & How to Apply Below

Amazon is a global technology company developing advanced robotics, machine learning, and artificial intelligence solutions for complex operational challenges. Amazon Robotics is seeking an Applied Scientist to develop and evaluate robotics foundation models, including vision-language-action, reasoning, task-planning, and reinforcement-learning models, while collaborating with scientists and engineers to advance intelligent robotic systems.

Responsibilities
  • Model Development and Training:
    Designing and implementing the model architectures, training and fine tuning the foundation models using various datasets, and optimize the model performance through iterative experiments
  • Data Management:
    Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines
  • Experimentation and Validation:
    Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance
  • Code Development:
    Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs
  • Research:
    Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions
  • Collaboration:

    Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies
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