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 into Deltas on premise and cloud Production environments
- Transform data science protypes and applying appropriate ML algorithms and tools
- Train and retrain ML models
- Develop deep learning systems to various use cases based on the business needs
- 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 Delta’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 Delta 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 Delta teams, with outside vendors or consultants to ensure project or product integrity
- Mentor other Senior Developers on the team

WHAT ARE WE LOOKING FOR?
- 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, Java, R, Scala, Spark 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, 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

WHAT ELSE?
- Functional knowledge of the airline business or airline IT processes
- An eye for detail
Delta Air Lines develops both strategic and tactical plans that create a safety-conscious environment resulting in employee safety and well-being.