Engineer 3, Machine Learning-5125

Comcast•Washington, DC

42d•$126,090 - $165,000•Hybrid

About The Position

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

Requirements

Master’s degree, or foreign equivalent, in Computer Science, Engineering, or related technical field
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
Performing CI/CD using Jenkins

Nice To Haves

Kubernetes
PyTorch
Tensorflow

Responsibilities

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
Represent the work team in providing solutions to technical issues associated with assigned projects