Job Summary

Job Description

DUTIES: Contribute to a team responsible for building, maintaining, and improving Machine Learning models to solve practical problems; build and train Machine Learning models, including Deep Learning models, using TensorFlow, PyTorch, Databricks, and Spark; gather data to train models using PySpark; use Airflow to orchestrate jobs created in Databricks; develop, test, and debug software using Python and command line tools; develop and maintain scalable APIs using Python; develop services to be deployed in microservice architecture, using Kubernetes, Helm Charts, AWS, and Istio; translate and optimize Machine Learning models, and report on Machine Learning model performance, using Prometheus, Grafana, Kubernetes, and Istio; translate feature designs and problems into Machine Learning models and software; perform source control using Git; work in an Agile development environment; perform CI/CD using GitHub Actions; contribute to both software engineering and machine learning sides of projects by implementing, refining, and validating machine learning algorithms for products and applications; take action on existing specifications of designs and develop data pipelines consisting of data ingest, data validation, data cleaning, and data monitoring; train machine learning models, validate the accuracy of the machine learning models once trained, and deploy validated machine learning models into production; research, write, and edit documentation and technical requirements, including evaluation plans, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports; create patents, including Application Programming Interfaces (APIs) and other intellectual property; test and evaluate solutions presented by various internal and external partners and vendors; complete case studies, testing, and reporting; design proof of concept solutions and contribute to studies to support future product or application development; collaborate with teams outside of immediate work group; and represent the work team in providing solutions to technical issues associated with assigned projects. Position is eligible to work remotely one day a week, per company policy.

REQUIREMENTS: Master's degree, or foreign equivalent, in Computer Science, Engineering, or related technical field, and one (1) year of experience building and training Machine Learning models, including Deep Learning models, using TensorFlow, PyTorch, Databricks, and Spark; gathering data to train models using Jenkins; developing, testing, and debugging software using Python and command line tools; developing and maintaining scalable APIs using Python; developing services to be deployed in microservice architecture, using Kubernetes, Helm Charts, AWS, and Istio; translating and optimizing Machine Learning models, and reporting on Machine Learning model performance, using Prometheus, Grafana, Kubernetes, and Istio; translating feature designs and problems into Machine Learning models and software; performing source control using Git; working in an Agile development environment; and performing CI/CD using Jenkins.

SALARY: $126,090 to $165,000 per year

BENEFITS: https://jobs.comcast.com/life-at-comcast/benefits

Disclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.

Skills
Kubernetes, PyTorch, Tensorflow

Compensation
Base Pay: $126,090.00

Comcast intends to offer the selected candidate base pay dependent on job-related, non-discriminatory factors such as experience.

Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.

The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.