Title:  Engineer Machine Learning Operations

Position Title: Machine Learning Operations Engineer

Position Summary

The Data Science & Analytics team at JetBlue is an integral part of the IT Data organization which reports directly to the Chief Digital & Technology Officer due to the strategic importance of Data at JetBlue. The Data Science & Analytics team consists of Operations Data Science (ODS), Commercial Data Science (CDS), Artificial Intelligence (AI) & Machine Learning (ML) engineering, and Business Intelligence teams operating in a center-of-excellence model reporting to the Senior Manager, Data Science & Analytics. The teams develop advanced Data products and insights for all cross-functional teams at JetBlue including up/cross-skilling the internal analyst community.

The Machine Learning Operations Engineer ­will be responsible for maintaining production-grade Machine Learning pipelines that deliver the best results with optimum deployment efficiencies. The Machine Learning Operations Engineer will collaborate with Data Science and Development Operations (DevOps) teams to build and maintain the infrastructure and Continuous Integration/Continuous Deployment (CI/CD) pipelines necessary to deploy and maintain AI and ML products at scale. The Machine Learning Operations Engineer reports to the General Manager, IT Data Science & Analytics.

Essential Responsibilities

• Collaborate with Architecture, Infrastructure and Data Science teams to translate their needs or challenges into production-grade Artificial Intelligence and Machine Learning deployment architectures for batch, real-time streaming and edge deployments

• Build CI/CD pipelines for ML models, AI products and data engineering pipelines with an emphasis on automated testing, version control, documentation and monitoring

• Optimize spark, torch and Databricks pipelines to meet latency, cost, reliability and scalability requirements

• Design and build automated unit tests and integration tests for ML models, AI products and data engineering pipelines

• Build and implement monitoring and alerting framework for AI deployments

• Effectively communicate architectures and technical details with partners

• Stay up-to-date with the latest trends and advancements in AI and ML and identify opportunities for the team to implement new models and technologies

• Follow an agile development methodology including Software Development Lifecycle (SDLC) framework

• Other duties as assigned

Minimum Experience and Qualifications:

• Bachelor’s Degree in computer science or a quantitative discipline; OR demonstrated capability to perform job responsibilities with a High School Diploma/GED and at least four (4) years of previous relevant experience

• Three (3) years of relevant industry experience

• Experience deploying and maintaining Artificial Intelligence and Machine Learning models including efficient deployment architectures based on industry best-practices

• Able to write production-grade code and be familiar with software engineering best practices, including testing, version control and CI/CD frameworks by working closely with internal DevOps teams

• Ability to successfully complete technical interviews in areas of deployment frameworks, Machine Learning, Python, PySpark and Machine Learning Operations

• Experience using CI/CD and DevOps technologies such as Kubernetes, Docker, Github Actions, Jenkins, Terraform, mlflow

• Proficiency in Python, Structured Query Language (SQL), git and common Data Science, Artificial Intelligence and Machine Learning libraries

• Available for occasional overnight travel (10%)

• Must pass a pre-employment drug test

• Must be legally eligible to work in the country in which the position is located

Preferred Experience and Qualifications

• Advanced degree in computer science or a quantitative discipline

• Five (5) years of relevant industry experience

• Experience deploying Artificial Intelligence and Machine Learning frameworks in: Forecasting, Recommendation Systems, A/B Testing, Logistics Optimization, Churn Analysis, Segmentation Analysis, Deep Learning and Natural Language Processing

• Experience building and implementing feature stores, vector databases, and custom Application Program Interfaces (APIs)

• Experience using Databricks, PyTorch, TensorFlow, Docker, Kubernetes, PySpark / Spark, Terraform, Snowflake, dbt, Azure Cloud, Flask, FastAPI

Crewmember Expectations:

• Regular attendance and punctuality

• Potential need to work flexible hours (including nights & weekends) and be available to respond on short-notice

• Able to maintain a professional appearance

• When working or traveling on JetBlue flights, and if time permits, all capable Crewmembers are asked to assist with light cleaning of the aircraft

• Must be an appropriate organizational fit for the JetBlue culture, that is, exhibit the JetBlue values of Safety, Caring, Integrity, Passion and Fun

• Promote JetBlue’s #1 value of safety as a Safety Ambassador, supporting JetBlue’s Safety Management System (SMS) components, Safety Policy and behavioral standards

• Identify safety and/or security concerns, issues, incidents or hazards that should be reported and report them whenever possible and by any means necessary including JetBlue’s confidential reporting systems (Aviation Safety Action Program (ASAP) or Safety Action Report (SAR))

Equipment:

• Computer and other office equipment

Work Environment:

• Traditional office environment

Physical Effort: 

• Generally not required, or up to 10 pounds occasionally, 0 pounds frequently. (Sedentary)

Compensation: 

• The base pay range for this position is between $117,500.00 and $150,400.00 per year. Base pay is one component of JetBlue’s total compensation package, which may also include access to healthcare benefits, a 401(k) plan and company match, crewmember stock purchase plan, short-term and long-term disability coverage, basic life insurance, free space available travel on JetBlue, and more.

#LI-LL1 #LI-Hybrid