Machine Learning Engineer-Atlanta, Georgia-Hybrid

Machine Learning Engineer - Atlanta, Georgia - Hybrid

Qualifications

• 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
• Knowledge of mining complex data (including structured and unstructured), identifying patterns, and feature engineering
• Experience with design patterns and implementation and deployment of 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
• Proficiency with Python, Java, Scala, Spark
• Experience developing, testing, and deploying APIs
• Experience building applications based on Microservices Architecture
• A solid understanding of large scale data processing platforms (Apache Spark, Apache Hadoop)
• 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)
• Experienced in using AI platforms and technologies (e.g. TensorFlow, Apache MXnet, Theano, Keras, CNTK, scikit-learn, H2O, Spark MLlib, etc)
• Experience with automating application deployment, continuous delivery, and continuous integration (Jenkins, Ansible)
• Experience with VersionOne, JIRA, GIT (GitLab, Bitbucket, or other)
• 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
• Functional knowledge of the airline business or airline IT processes
• An eye for detail

Responsibilities

• The Client engineer will take models developed by the data scientists and integrate them 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 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 Delta's on-premise and cloud Production environments
• Transform data science prototypes and apply appropriate Client algorithms and tools
• Train and retrain Client models
• Develop deep learning systems for various use cases based on business needs
• Automate model training, 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
• Optimize 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 teams and other Delta teams, with outside vendors or consultants to ensure project or product integrity
• Mentor other Senior Developers on the team