We are looking for a Machine Learning Engineer who can bring bleeding edge machine learning and optimization models into production together with a highly multi-disciplinary team of data scientist, software development engineers, strategic partners, product managers and subject domain experts. The ML engineer will take models developed by the data scientists and integrate it in with the rest of the company’s platform. This could involve building an API around the model so that it can be served and consumed, and then being able to maintain the integrity and quality of this model so that it continues to serve accurate predictions. This position can be in Minneapolis or Atlanta.
YOUR RESPONSIBILITIES IN THIS ROLE
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 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 client’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 client 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 client teams, with outside vendors or consultants to ensure project or product integrity
- Mentor other Senior Developers on the team
WHAT ARE WE LOOKING FOR? / WHAT EXPERIENCE DO YOU NEED?
- 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 Spring Boot
- 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
- Candidate must be solutions oriented using rigorous logic and methods to solve difficult problems with effective solutions, probing all sources for answers.
- Candidate must also have excellent written and verbal skills with the ability to communicate effectively with all levels of employees and management.
- Additionally, candidate must be a self-learner with the ability to pick up new technologies and provide tangible results. –
- Strong problem-solving skills and capability to understand and set direction for complex technology integration
- Understanding and focus on business outcomes - Strong teamwork skills