Machine Learning Engineer 3

Comcast - Philadelphia, PA

Full-time

Remote - Philadelphia, PA

Broadcasting and Content Providers

About the position

The position involves developing and deploying machine learning algorithms and mathematical optimization solutions, which include mathematical programming techniques such as linear and mixed integer programming, as well as decomposition techniques. The role requires writing production code and applying statistical knowledge for effective planning and forecasting. A strong proficiency in Python and Git is essential, as well as the ability to create time series forecasts and utilize SQL for data analysis. The candidate will also perform distributed computing using Spark and TensorFlow, ensuring the accuracy and functionality of the machine learning algorithms developed. In addition to these technical skills, the role requires translating application requirements into machine learning and mathematical optimization problem statements. The candidate will analyze and evaluate solutions that are both internally generated and supplied by third parties. A key aspect of the job is to develop innovative ways to leverage machine learning for problem-solving and product discovery. The successful candidate will implement, refine, and validate machine learning algorithms and mathematical optimization solutions for various products and applications. The position also involves taking action on existing design specifications and developing comprehensive data pipelines that include data ingestion, validation, cleaning, and monitoring. Training machine learning models, validating their accuracy post-training, and deploying these validated models and optimization solutions into production are critical responsibilities. Furthermore, the candidate will be tasked with researching, writing, and editing documentation and technical requirements, which encompass evaluation plans, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations, and reports. Testing and evaluating solutions presented by various internal and external partners and vendors, as well as designing proof of concept solutions, will also be part of the role to support future product or application development. This position is eligible for 100% remote work.

Responsibilities

• Develop and deploy machine learning algorithms.
• Develop and deploy mathematical optimization solutions, including mathematical programming techniques.
• Write production code using Python.
• Apply statistical knowledge for planning and forecasting.
• Use Git for version control.
• Create time series forecasts.
• Analyze data using SQL.
• Perform distributed computing using Spark and TensorFlow.
• Evaluate accuracy and functionality of machine learning algorithms.
• Translate application requirements into machine learning and mathematical optimization problem statements.
• Analyze and evaluate solutions from internal and external sources.
• Develop novel ways to use machine learning for problem-solving and product discovery.
• Implement, refine, and validate machine learning algorithms and mathematical optimization solutions.
• Develop data pipelines for data ingest, validation, cleaning, and monitoring.
• Train machine learning models and validate their accuracy.
• Deploy validated machine learning models and optimization solutions into production.
• Research, write, and edit documentation and technical requirements.
• Test and evaluate solutions from internal and external partners and vendors.
• Design proof of concept solutions and contribute to studies for future product development.

Requirements

• Master's degree, or foreign equivalent, in Computer Science, any Engineering, Statistics, Data Science, Physics, Applied Mathematics, or a related technical or scientific field.
• One (1) year of experience developing and deploying machine learning algorithms and mathematical optimization solutions, including linear programming and mixed integer programming.
• Experience writing production code using Python.
• Experience applying statistical knowledge to planning and forecasting.
• Experience performing version control using Git.
• Experience creating time series forecasts.
• Experience analyzing data using SQL.
• Experience performing distributed computing using TensorFlow.