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Senior Machine Learning Scientist – GenAI & Agentic AI

SpringCube

Full time - Senior Engineer

Retail & Ecommerce

United States, Boston - Massachusetts

Published 2 weeks ago

Salary: Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A leading global e-commerce and technology company is focused on enabling customers to live in homes they love. The organization invests heavily in AI and machine learning, developing advanced agentic AI systems across supply chain, customer service, catalog management, and merchandising. The company fosters a culture of innovation, collaboration, and technical excellence to deliver high-impact solutions at scale.

Summary
The Senior Machine Learning Scientist will define and drive the technical strategy, system design, and evaluation frameworks for generative and agentic AI systems. This high-impact role involves shaping AI architectures, mentoring scientists, and delivering production-level AI solutions that influence business outcomes across multiple departments.

Responsibilities

  • Partner with leadership to set company-wide technical strategy for agentic AI systems, defining architectural standards and best practices
  • Lead design of agentic AI systems across supply chain, customer service, supplier and carrier outreach, physical retail, catalog management, and merchandising operations
  • Identify where agentic AI adds value and recommend alternative ML or automation solutions when more appropriate
  • Design and standardize evaluation frameworks including task success, business impact metrics, quality and failure analysis, human-in-the-loop review, and online/offline evaluation
  • Establish rigorous approaches to trust, safety, and governance for agentic AI systems
  • Tech-lead production GenAI products, unifying architectures and implementation patterns to accelerate development and maintenance
  • Guide teams on agent orchestration, multi-agent coordination, and cross-agent communication
  • Provide senior-level technical leadership through architecture and code reviews
  • Collaborate with senior business, product, and technology stakeholders to translate ambiguous problems into AI solutions
  • Communicate complex GenAI concepts and influence decisions across the organization
  • Stay current with LLMs, agentic AI, LLMOps, and related advancements, introducing new techniques for business impact
  • Mentor and grow other ML scientists, raising the overall bar for GenAI excellence

Qualifications

  • PhD with significant industry experience, or Master’s in Computer Science, AI, ML, or related quantitative field with 10+ years applied ML experience, including senior or staff-level technical leadership
  • Deep expertise in Generative AI, LLMs, and agentic AI systems with hands-on production experience
  • Proven ability to design end-to-end AI systems from problem formulation through deployment and evaluation
  • Strong software engineering skills in Python; familiar with PyTorch, TensorFlow, Langgraph, ADK, data systems, and AIops infrastructure
  • Experience influencing technical direction across multiple teams without direct authority
  • Understanding of agent architectures, trade-offs between flexibility and deterministic execution, LLMOps, CI/CD, monitoring, and automated evaluation
  • Experience building scalable data pipelines and collaborating with platform teams
  • Track record of designing robust evaluation frameworks for complex, non-deterministic AI systems
  • Exceptional communication skills for technical and non-technical audiences
  • Ability to challenge assumptions, push back on stakeholders, and guide teams toward high-value solutions
  • Passion for mentorship, technical excellence, and building scalable, durable AI systems

Nice to Have

  • Prior experience defining GenAI or agentic AI strategy at a large organization
  • Publications or thought leadership in AI, ML systems, or applied GenAI
  • Experience with AI trust, safety, or governance frameworks
  • Familiarity with large-scale distributed systems and multi-tenant ML platforms

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.