Machine Learning Engineer

XUMO (Comcast) is seeking a highly experienced Machine Learning Engineer to design, train, and deploy machine learning models that power recommendation capabilities. This hybrid role in Irvine, CA focuses on personalization algorithms built on large-scale data, with responsibilities spanning modeling, evaluation, data pipelines, and cross-team integration.

Responsibilities

• Develop and improve machine learning algorithms for integration across products and applications, aligned to specifications and data pipeline architectures.
• Lead training of machine learning models, including validation and deployment into production systems.
• Create and maintain data pipelines that support efficient data ingestion, validation, cleaning, and ongoing monitoring.
• Produce documentation and technical requirements, including evaluation plans, white papers, and reports.
• Contribute to patents, Application Programming Interfaces (APIs), and other intellectual property.
• Assess machine learning solutions from internal and external partners by leading testing and assessment initiatives.
• Run deep-dive case studies and compile findings to inform product development and testing strategies.
• Design proof of concept solutions and direct studies that support future product or application advancement.
• Collaborate with cross-functional teams to provide technical solutions for complex issues tied to assigned projects.
• Provide guidance and mentorship to junior engineers and set a technical example within the team.
• Develop and train sophisticated machine learning algorithms and implement the core recommendation system to increase product engagement through collaboration with multiple systems.
• Analyze big data to generate algorithmic insights.
• Work with product and operations teams to translate business requirements into algorithmic solutions, documenting model architectures and logic.
• Rapidly prototype new recommendation concepts and algorithms, validating mathematical approaches and transitioning experimental models into production-ready code.
• Implement, tune, and scale advanced machine learning models and multi-algorithm A/B testing logic to develop the core intelligence of the recommendation system.
• Partner with backend and client engineering teams to integrate models, prioritize algorithmic enhancements, and define approaches for model serving and latency reduction.
• Create technical documentation covering algorithm behavior, model dependencies, and requirements for system integration with the recommendation engine.
• Drive decisions on model selection, hyperparameter optimization, and feature engineering to address complex business problems and improve personalized content delivery.
• Engineer feature sets and training data schemas optimized for recommendation algorithm training and serving.
• Execute offline evaluations and online A/B tests, producing insights into performance against established baselines and benchmarks.
• Drive results and growth, and support a culture of inclusion in day-to-day work and leadership.

Requirements

• 3+ years of experience using statistical computer languages (Python, R, etc.).
• 3+ years of experience manipulating big data (BigQuery, etc.).
• 3+ years of experience operating databases (MySQL, PostgreSQL, Oracle, MongoDB).
• Experience and knowledge of developing multiple machine learning techniques including clustering, decision tree learning, and artificial neural networks, including real-world advantages and drawbacks.
• Experience and knowledge of advanced statistical techniques and concepts such as regression, properties of distributions, statistical tests, and appropriate application.
• Strong problem-solving skills with emphasis on product development.
• Excellent written, drawing, and verbal communication skills for coordinating across teams.
• Strong leadership in designing and implementing approaches for new features and problem solving.
• Self-starter capable of producing high-quality output with minimal supervision.
• Aggressive learner for new technologies and techniques.
• Role location: office-based in Irvine, CA, 4 days/week in office and 1 day remote.

Technologies

• Python, R
• BigQuery
• MySQL, PostgreSQL, Oracle, MongoDB
• Big data
• clustering, decision tree learning, artificial neural networks, regression, statistical tests
• Google Cloud, AWS, Azure
• Spark
• Linux-based operating system, CentOS, OSX
• A/B testing
• machine learning frameworks

Desirable Experiences

• Experience operating servers in cloud environments (Google Cloud, AWS, Azure).
• Experience with data processing frameworks (Spark).
• Experience working with Linux-based operating systems (CentOS, OSX).
• Experience developing scalable and highly available applications.
• Experience with recommendation services.

Skills

• Collaboration
• Algorithms
• Recommendation Engines
• Business Problems

Education

Bachelor's Degree

Experience Level

5-7 Years

Salary

Pay range: This job can be performed in California with a good faith estimated pay range upon hire of $142,651.46 - $190,201.94 USD.

Location and Schedule

Irvine, CA (hybrid): 4 days/week in office and 1 day remote.

Minimum Experience

3 years