2 месяца назад
Sr. Software Dev Engineer, SageMaker AI
168 100 - 227 400$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Sr. Software Dev Engineer, SageMaker AI (LLM/data preparation): Building scalable data quality and evaluation systems for machine learning workflows with an accent on auto-labeling, human-in-the-loop verification, and LLM-as-Judge techniques. Focus on architecting distributed ML infrastructure, establishing quality standards for AI agents and models, and continuously improving training data at human quality and machine scale.
Location: Onsite in Seattle, Washington, USA.
Salary: $168,100–$227,400 USD annually, plus sign-on payments, restricted stock units, and comprehensive benefits.
Company
Amazon Web Services develops and operates a broad cloud platform, including managed machine learning and data preparation services.
What you will do
- Design and deliver core data preparation components for customizing and fine-tuning large language models.
- Build scalable auto-labeling and LLM-as-Judge systems that detect, diagnose, and remediate data quality issues.
- Establish quality standards and evaluation frameworks for AI agents and machine learning models.
- Develop human-in-the-loop services for data labeling, annotation quality assurance, and ground-truth generation.
- Make architectural decisions across distributed systems, data processing, and ML infrastructure while owning the technical roadmap.
- Mentor engineers, lead design reviews, and influence technical direction across the team.
Requirements
- 5+ years of professional, non-internship software development experience.
- 5+ years of programming experience with at least one software programming language.
- 5+ years of leading the design or architecture of reliable and scalable systems.
- Experience mentoring engineers, serving as a tech lead, or leading an engineering team.
- Experience with the full software development life cycle, including coding standards, code reviews, source control, build processes, testing, and operations.
- Bachelor’s degree in computer science or equivalent experience.
Nice to have
- Experience building ML pipelines, data processing systems, or evaluation infrastructure at scale.
- Hands-on experience with LLM prompting, fine-tuning, structured output, and confidence calibration.
Culture & Benefits
- Knowledge-sharing, mentorship, and thorough code reviews support engineering growth.
- Flexible working practices support work-life harmony.
- Benefits include medical, dental, vision, prescription, life and AD&D insurance, mental health support, flexible spending accounts, and 401(k) matching.
- Paid time off, parental leave, and adoption and surrogacy reimbursement are available.
- Employee-led affinity groups and inclusion-focused learning events support a diverse workplace.
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