Design and implement business-critical features and contribute to optimizing the performance of models on AWS Trainium end to end, focusing on LLM model families like GLM and Kimi.
Compensation
USA, CA, Cupertino - 127,100.00 - 185,000.00 USD annually
Responsibilities
Optimize open models to run best on Trainium, including optimizing sharding, developing NKI kernels and ensuring accuracy.
Collaborate with cross-disciplinary teams that may include hardware design, firmware, compiler, runtime, and ML engineers to develop software that enables and optimizes custom ML accelerator silicon.
Write clean, maintainable code (C/C++, Python, or Rust) following best practices for systems-level and performance-critical development.
Participate in code reviews, contribute to technical documentation, and help deploy agentic tools to accelerate the enablement of new models on Trainium.
Demonstrate operational excellence through monitoring, debugging, and resolving issues across hardware-software integration boundaries, including on-call responsibilities.
Requirements
Bachelor's degree or above in Computer Science, Computer Engineering, Electrical Engineering, or related fields
Develop and implement community standards for genome sequences and metadata from single-cell microeukaryotes, microbial symbioses, and co-cultures.
Compensation
The salary range for this position is $6,048 - $6,743 monthly / $72,576 - $80,916 annually and is expected to start at $6,048 monthly / $72,576 annually or above.
Responsibilities
Develop community genome and metadata standards
Collaborate with Genomic Standards Consortium and stakeholders
Conduct targeted genome quality and metadata assessments
Create controlled vocabularies, templates, checklists, and guidelines
Identify reporting gaps and improve validation
Requirements
Ph.D. in Computational Biology, Bioinformatics, Microbiology, Molecular Biology, or related discipline
Remote Sensing and Overhead Persistent Infrared (OPIR) Subject Matter Expert to inform the design, implementation, and testing of infrared-sensing and space-based missile-warning systems, data-exploitation capabilities, and advanced algorithms.
Compensation
The salary range for this position is $141,000 to $212,000 annually. This position is also eligible for a discretionary performance-based bonus and stock based compensation.
Responsibilities
Define operational needs in coordination with government leaders, research and development teams, and operations analysts
Lead the prototyping and development of advanced OPIR data-processing algorithms and support their transition to operational environments
Evaluate and troubleshoot data-processing pipelines, identify anomalies, and coordinate remediation strategies
Prepare and deliver white papers, technical reports, and briefings
Collaborate with research organizations, Department of Defense stakeholders, Intelligence Community organizations, and other external agencies
Requirements
Bachelor’s degree in remote sensing, engineering, mathematics, physics, or a related technical field
Nice to have: Master’s degree or PhD in remote sensing, engineering, mathematics, physics, or a related technical field
Nice to have: Direct experience performing OPIR analysis
Nice to have: Experience collaborating with the National Geospatial-Intelligence Agency (NGA), National Air and Space Intelligence Center (NASIC), or other Intelligence Community organizations
Be part of a dynamic and Agile team that designs, develops, and integrates complex software functions/Tools to support accelerated product development.
Responsibilities
Design, develop, and integrate complex software functions and tools
Focus on growth, productivity, cycle time improvement and generate innovative solutions
Design, implement, validate, and productionize algorithms that transform complex scientific and operational data into actionable insights, focusing on analytical and algorithmic layers consuming curated data.
Responsibilities
Design, develop, and maintain algorithms for processing, analyzing, and modeling scientific and operational data.
Develop robust Python-based computational workflows using appropriate scientific computing, data analysis, and machine learning libraries.
Analyze complex datasets to identify patterns, derive meaningful features, and develop predictive or diagnostic insights.
Develop and optimize algorithms for areas such as signal processing, image analysis, anomaly detection, predictive analytics, and other data-driven applications.
Evaluate algorithm performance through systematic testing, validation, benchmarking, and comparison against defined performance criteria.
Requirements
Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, Electronics, Engineering, or a related technical discipline
Experienced Software Engineer to design, implement, validate, and productize algorithms transforming complex diagnostics and operational data into actionable insights, focusing on analytical and algorithmic layers migrating from AWS to Databricks.
Responsibilities
Develop and maintain algorithms for processing, analyzing, and modeling machine diagnostics and operational data.
Build Python-based computational workflows using appropriate scientific computing and data analysis.
Analyze complex datasets to identify patterns, derive useful features, and support predictive or diagnostic insights.
Develop and improve algorithms in areas such as signal processing, image analysis, anomaly detection, predictive analytics, and other data-driven applications.
Perform algorithm testing, validation, benchmarking, and performance evaluation against defined criteria.
Requirements
Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, Electronics, Engineering, or a related technical discipline.
Contribute to the design, implementation, validation, and productization of algorithms that transform complex diagnostics and operational data into actionable insights.
Responsibilities
Develop and maintain algorithms for processing, analyzing, and modeling machine diagnostics and operational data.
Build Python-based computational workflows using appropriate scientific computing and data analysis.
Analyze complex datasets to identify patterns, derive useful features, and support predictive or diagnostic insights.
Develop and improve algorithms in areas such as signal processing, image analysis, anomaly detection, predictive analytics, and other data-driven applications.
Perform algorithm testing, validation, benchmarking, and performance evaluation against defined criteria.
Requirements
Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, Electronics, Engineering, or a related technical discipline.
Senior Machine Learning EngineerApple · Sunnyvale, US
Microbial Genomics Postdoctoral FellowLawrence Berkeley National Laboratory · Berkeley, US