> Markdown version of [/jobs/ext/2407923-engineer-3-machine-learning](https://www.wearedevelopers.com/jobs/ext/2407923-engineer-3-machine-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Engineer 3, Machine Learning - **Company:** Xfinity - **Location:** Washington, DC, United States (Remote available) - **Experience:** Expert - **Salary:** $126,090.0 - $165,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Confluence, Command-Line Interface, Continuous Integration, Data Validation, Data Cleansing, Data Control, Software Debugging, Github, Python (Programming Language), Machine Learning, Tensorflow, Prometheus, Software Engineering, Pytorch, Istio, Grafana, Apache Spark, Deep Learning, Kubernetes Helm Charts, Git, Pyspark, Kubernetes, Information Technology, Restful APIs, Software Version Control, Data Pipelines, Jenkins, Databricks, Microservices - **Published:** August 17, 2026 - **Apply:** https://www.careerjet.com/job/usef7d49c80f627de762215fee3afb151a/eaa ## About the Role 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, Kubernetes; PyTorch; Tensorflow ## 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., Distinguished AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an indus… + 2 days ago, Lead Machine Learning Engineer (Manager IC) At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. 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