Applied Scientist, Satellite Manufacturing AI

Socket.dev; Bellevue (WA); On-site; USD 143,000 - 193,000; Full time

Job summary

Socket.dev is hiring an Applied Scientist to build the scientific intelligence layer powering satellite manufacturing systems. You will develop ML models to transform fragmented manufacturing and quality data into actionable intelligence, enabling AI-enabled workflows and reducing defects in production.

You will tackle high-impact problems with incomplete or noisy data, deploying models and contributing to production pipelines with rigorous experimentation and documentation.

Qualifications

• 3+ years building models for business applications.
• PhD or Master’s degree with 4+ years in CS/CE/ML or related field.
• Publications or patents at top-tier conferences/journals.
• Programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, HPC.

Responsibilities

• Translate ambiguous manufacturing problems into well-defined scientific problems and criteria.
• Design, train, and deploy ML models including LLM-based systems and retrieval models.
• Develop and evaluate models with large-scale, noisy, heterogeneous data.
• Apply state-of-the-art techniques in anomaly detection, root-cause inference, multimodal learning, and information retrieval.
• Design experiments and evaluation frameworks that capture real-world failure modes and risks.
• Build production-quality scientific components with testing and monitoring.

Skills

Java

C++

Python

PhD or MS + CS/ML/CE

Publications or patents

NLP

Information retrieval

Multimodal learning

Anomaly detection

Generative AI

LLM deployment

RAG

Education

PhD

Master's degree

Tools

Unix/Linux

Professional software development

Cloud / AI infra

Job description

Socket.dev is hiring an Applied Scientist to build the scientific intelligence layer powering satellite manufacturing systems. You will develop ML models to transform fragmented manufacturing and quality data into actionable intelligence, enabling AI-enabled workflows and reducing defects in production.

You will tackle high-impact problems with incomplete or noisy data, deploying models and contributing to production pipelines with rigorous experimentation and documentation.