Applied Scientist, Satellite Build Systems AI

Amazon; El Segundo (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Amazon Leo Satellite Build Systems is seeking an Applied Scientist to translate manufacturing problems into rigorous ML problems and to design, train, and deploy large-scale models. You will work with cross-functional teams to prototype and productionize ML solutions that improve manufacturing outcomes.

You will leverage state-of-the-art techniques across anomaly detection, information retrieval, multimodal learning, and generative AI, while balancing model quality with latency and cost.

Qualifications

• 3+ years of building models for business applications.
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• Experience in patents or publications at top-tier peer-reviewed conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Responsibilities

• Translate ambiguous manufacturing and operational problems into well-defined scientific problems, modeling approaches, and evaluation criteria.
• Design, train, and deploy machine learning models, including LLM-based systems, retrieval models, and task-specific models
• Develop and evaluate models using large-scale, noisy, heterogeneous datasets with incomplete, delayed, or imperfect ground truth
• Apply state-of-the-art techniques in areas such as anomaly detection, root-cause inference, multimodal learning, information retrieval, and generative AI, adapting or extending them to meet project requirements
• Design experiments and evaluation frameworks that capture real-world failure modes, distribution shift, and decision risk
• Make principled tradeoffs among model complexity, data quality, accuracy, latency, cost, and maintainability
• Build production-quality scientific components with appropriate testing, documentation, monitoring, and operational mechanisms
• Work with Manufacturing, Quality, Test, and engineering partners to understand customer needs and translate them into effective scientific solutions
• Analyze model and system performance, identify gaps and root causes, and iteratively improve deployed solutions
• Clearly document scientific approaches, experimental results, design decisions, and lessons learned so that others can understand and reproduce the work
• Contribute to technical discussions, mentor less experienced teammates, and help advance scientific and engineering best practices within the team

Skills

Python

Java

C++

ML

Pytorch

Data mining

Optimization

Distributed computing

Research publication

Education

PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience

Job description

Amazon Leo Satellite Build Systems is seeking an Applied Scientist to translate manufacturing problems into rigorous ML problems and to design, train, and deploy large-scale models. You will work with cross-functional teams to prototype and productionize ML solutions that improve manufacturing outcomes.

You will leverage state-of-the-art techniques across anomaly detection, information retrieval, multimodal learning, and generative AI, while balancing model quality with latency and cost.