Machine Learning Engineer — End-to-End Production ML

Comcast Corporation; Indiana; On-site; USD 120,000 - 180,000; Full time

Job summary

Comcast Corporation is seeking a Machine Learning Engineer to independently deliver ML features and own components of production ML systems. This role emphasizes end-to-end ownership, sound technical judgment, and collaboration across teams.

You will design, build, deploy, and operate ML features and services, taking responsibility from experimentation to production monitoring, ensuring reliability and cost efficiency while aligning with product requirements.

Qualifications

• Strong foundations in data structures, algorithms, and statistics.
• Experience building, deploying, and operating production ML systems.
• Proficiency in at least one ML or deep learning framework.
• Ability to translate ambiguous requirements into concrete technical solutions.
• Strong communication and collaboration skills.

Responsibilities

• Design, build, deploy, and operate machine learning features and services end-to-end.
• Own ML pipelines and model behavior from experimentation through production monitoring.
• Solve complex ML and system-level problems independently.
• Participate in technical design discussions and influence implementation decisions.
• Improve performance, reliability, scalability, and cost efficiency of ML systems.
• Collaborate with cross-functional partners to translate product requirements into ML solutions.
• Design, build, and own LLM-based features, including prompt strategies, evaluation pipelines, chatbots, or agent workflows.
• Select and apply LLM frameworks (e.g., LangChain, LlamaIndex) and agent frameworks (e.g., OpenAI SDK, ADK, Autogen) based on use-case requirements and tradeoffs.

Skills

Data structures

Algorithms

Statistics

Production ML systems

ML frameworks

Tools

LangChain

LlamaIndex

OpenAI SDK

ADK

Autogen

Job description

Comcast Corporation is seeking a Machine Learning Engineer to independently deliver ML features and own components of production ML systems. This role emphasizes end-to-end ownership, sound technical judgment, and collaboration across teams.

You will design, build, deploy, and operate ML features and services, taking responsibility from experimentation to production monitoring, ensuring reliability and cost efficiency while aligning with product requirements.