Machine Learning Engineer

XUMO (Comcast) is seeking a highly experienced Machine Learning Engineer to design, train, and deploy advanced machine learning algorithms for a recommendation system. The position emphasizes personalization using large-scale data, with end-to-end model development, evaluation, and production deployment in collaboration with cross-functional partners.

Responsibilities

• Develop and enhance machine learning algorithms for product and application integration, aligned to specifications and data pipeline architectures.
• Lead model training, manage validation, and deploy models into production systems.
• Create and maintain data pipelines to support efficient ingestion, validation, cleaning, and ongoing monitoring.
• Produce comprehensive documentation and technical requirements, including evaluation plans, white papers, and reports.
• Contribute to patents, Application Programming Interfaces (APIs), and other intellectual property.
• Evaluate machine learning solutions from internal and external partners by leading testing and assessment initiatives.
• Conduct in-depth case studies and compile findings to inform product development and testing strategies.
• Design and develop proof of concept solutions and direct studies that support future product or application advancement.
• Collaborate with cross-functional teams to deliver technical solutions to complex issues tied to assigned projects.
• Provide guidance and mentorship to junior engineers and set a strong technical example.
• Develop and train sophisticated recommendation algorithms that power the core recommendation system and coordinate with multiple systems to improve product engagement.
• Analyze large-scale data to derive algorithmic insights.
• Partner with product and operations teams to translate business requirements into algorithmic solutions, documenting model architecture and logic.
• Rapidly prototype new recommendation concepts and algorithms, validating mathematical approaches and promoting experimental models into production-quality code.
• Implement, tune, and scale advanced machine learning models and the logic for multi-algorithm A/B testing.
• Work 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 algorithmic behavior, model dependencies, and requirements for system integration with the recommendation engine.
• Drive model selection, hyperparameter optimization, and feature engineering decisions to address complex business problems and improve personalized content delivery.
• Engineer feature sets and training data schemas optimized for recommendation training and serving.
• Execute rigorous offline evaluations and online A/B tests, comparing performance against baselines and benchmarks.
• Drive outcomes related to results and growth.
• Support a culture of inclusion through day-to-day work and leadership.

Requirements

• 3+ years’ experience using statistical computer languages (Python, R, etc.).
• 3+ years’ experience manipulating big data (BigQuery, etc.).
• 3+ years’ experience operating databases (MySQL, PostgreSQL, Oracle, MongoDB).
• Experience and knowledge developing multiple machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) including real-world advantages and drawbacks.
• Experience and knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage) with applications.
• Strong problem-solving skills with emphasis on product development.
• Excellent written, drawing, and verbal communication skills for cross-team coordination.
• Strong leadership in designing and implementing solutions for new features and problem solving.
• Self-starter who can deliver high-quality output with minimal supervision.
• Aggressive learner for new technologies and techniques.
• Office-based role in Irvine, CA: 4 days per 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 systems, 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

Compensation

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

Irvine, CA (hybrid)

Minimum Experience and Education

• Minimum experience: 3 years
• Relevant work experience: 5-7 Years
• Education: Bachelor’s Degree