We are looking for a Machine Learning Engineer to join our team for a long-term contract opportunity!
Position: Machine Learning Engineer
Location: Atlanta, GA or Minneapolis, MN
Term: 6 months++
- This position will partner with Data Scientists and Data Engineers to operationalize models and deliver insights to the business.
- Take responsibility for ensuring that Machine Learning code, models and pipelines are deployed successfully into production, and troubleshooting issues that arise.
- Continuously integrate and ship code into company's on premise and cloud Production environments.
- Automate model training and testing and deployment via machine learning continuous delivery pipelines.
- Build data APIs and data delivery services that support critical operational and analytical applications for company's internal business operations, customers and partners.
- Ensure a good data flow between database and backend systems.
- Design and implement metrics to verify model and algorithm effectiveness.
- Optimizing solutions for performance and scalability.
- Define KPIs and acceptance criteria for model performance in production.
- Ensure that the company's methodology, standards and procedures are adopted and implemented.
- Ensure that the technical solutions meet the customers' business goals and that customer satisfaction with the project and conclusion is high.
- Act as a Point of contact for technical issues, creating documentation, monitoring service levels.
- Coordinate activities with internal/external technology owners/service providers.
- Consult within project team and other company's teams, with outside vendors or consultants to ensure project or product integrity.
- Mentor other Senior Developers on the team.
Is this a fit:
- 6 + years of experience required
- The Machine Learning Engineer position requires a BS/MS degree, preferably in a technical or scientific field.
- 5+ years of experience in designing, developing, integrating and running business, big data and/or data science applications.
- Expert familiarity with of a variety of classic and modern machine learning techniques including deep learning, clustering, decision tree, classification, regression and neural networks.
- Knowledge of mining complex data (including structure and unstructured), identifying patterns, and feature engineering.
- Experience with design patterns and implementation and deployment AI and/or data science products.
- Experienced with deploying and managing infrastructures based on Docker, Kubernetes, or OpenStack, and Clouds such as OpenShift, Azure, AWS or Google Cloud Platform.
- Knowledge of data engineering and experience with big data.
- Linux and shell scripting expertise.
- Proficiency with SQL and NoSQL databases.
- Proficiency with scalable data extraction tools (e.g. Cassandra, MongoDB).
- Proficiency with Python, R, Scala, Spark, Java and/or SAS.
- Experience developing, testing and deploying APIs.
- Experience building applications based on Microservices Architecture.
- Experience with Spring Framework: Core, Integration, MVC and SpringBoot.
- A solid understanding of large scale data processing platforms (Apache Spark, Apache Hadoop).
- Experienced in using AI/ML platforms, technologies, techniques (e.g. TensorFlow, Apache MXnet, Theano, Keras, CNTK, scikit-learn, H2O, Spark MLlib, etc.).
- Experience with VersionOne, JIRA, Confluence, GIT(gitlab, Bitbucket or other.).
- Experience with automating application deployment, continuous delivery, and continuous integration (Jenkins, Ansible).
- Experience using Agile/Scrum methodologies.
If this sounds like you, please apply to MATRIX today!