Comcast
media and technology
Engineer4-MachineLearning
Neural analysis suggests this role is
optimal for Senior candidates.
“Engineer 4 - Machine Learning at Comcast. Skills: Machine Learning, LLM, System Design. Direct advanced machine learning projects. Set goals for projects”
Industry & Context.
Systems thinking; Architectural judgment
What They're Looking For.
Must Have
Deep experience building and operating large-scale, production ML systems, Expertise in one or more ML domains (e.g., NLP, computer vision, forecasting), Hands-on experience with LLM frameworks such as LangChain or LlamaIndex, Proven experience designing and deploying agent-based systems using frameworks such as OpenAI SDK, ADK, or Autogen, Proven ability to lead technically without direct people management, Systems thinking and architectural judgment, Excellent communication skills across technical and non-technical audiences, 7-10 Years Relevant Work Experience
Nice to Have
Some combination of coursework and experience, or who have extensive related professional experience
What You'll Do.
Direct advanced machine learning projects
Set goals for projects
Manage sophisticated solutions
Author critical documentation
Own design and evolution of ML services
Drive technical strategy
Drive architectural decisions
Lead delivery of ML initiatives
Define best practices for model development
Define best practices for model evaluation
Define best practices for model deployment
Define best practices for model monitoring
Establish standards for prompt engineering
Establish standards for LLM evaluation
Establish standards for agent design
Improve system reliability
Improve system scalability
Improve system maintainability
Represent ML technical decisions
Drive framework strategy
Drive platform strategy
How You'll Work.
Team & Collaboration
Represent ML technical decisions in cross-team discussions; Represent ML technical decisions in cross-organization discussions
Communication Scope
Excellent communication skills across technical and non-technical audiences
Process & Methodology
Lead delivery of complex ML initiatives from problem definition through production
Full Job Description
Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. **Job Summary** This job entails directing advanced machine learning projects for decision automation and pattern recognition. It includes setting goals, designing prototypes, and leading research. The role manages sophisticated solutions, authors critical documentation, and mentors engineers. High-level machine learning expertise and innovation capacity are essential. **Job Description** ## **Role Overview** We are looking for a Senior Machine Learning Engineer to lead the technical design and delivery of ML systems and platforms. This role focuses on architectural ownership, technical leadership, and raising the engineering bar across teams. Responsibilities • Own the design and evolution of critical ML services, platforms, or system components. • Drive technical strategy and architectural decisions for ML and LLM-powered systems. • Lead delivery of complex ML initiatives from problem definition through production. • Define best practices for model development, evaluation, deployment, and monitoring. • Establish standards for prompt engineering, LLM evaluation, safety, and agent design. • Mentor engineers through design reviews, code reviews, and technical guidance. • Improve system reliability, scalability, and long-term maintainability. • Represent ML technical decisions in cross-
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