Senior Machine Learning Engineer
About The Position
The Senior Machine Learning Engineer will embed within the centralized ML team and support the Customer Intelligence CBI productionization initiative. This role involves taking ownership of productionizing ML pipelines, including code refactoring and system optimization. The engineer will collaborate closely with data scientists, data engineers, and product partners to accelerate the delivery of scalable, production-ready ML solutions. The team is a centralized Machine Learning team supporting 7 business units, consisting of Senior to Principal-level Data Scientists, fostering a collaborative, supportive, and high-performing culture with a strong focus on quality, innovation, scalability, and measurable revenue impact.
Requirements
- Master’s/PhD degree with 3 years of experience in a quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.)
- Experience with Python programming language
- Practical experience with data extraction, cleaning, and analysis
- Depth of knowledge in statistical and machine learning techniques
- Strong Python expertise (production-grade coding, modularization, testing, performance tuning)
- Hands-on experience with Machine Learning pipeline development and productionization (model deployment, orchestration, monitoring, and optimization)
- Ability to effectively communicate both verbally and written with all levels within the organization
- Demonstrated motivation and aptitude for logical analysis, problem identification, and problem solving
- Ability to view data from different angles to employ feature engineering techniques to better represent models
- Ability to work on a diverse team with diverse skillsets
Nice To Haves
- 8 years of experience in a technical professional environment, in addition to the minimum requirements
- Experience with SQL and data visualization (Tableau, PowerBI)
- Practical experience designing, building and deploying machine learning models
- Experience in using cloud platforms and parallel processing to scale model development/ deployment (Databricks, Azure)
- Domain knowledge in the airline industry
- Experience working in a consulting role
- Experience with Databricks / Spark-based ML pipelines
- Proficiency in SQL and working with large-scale datasets
- Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
Responsibilities
- Productionize ML pipelines, including code refactoring and system optimization.
- Collaborate with data scientists, data engineers, and product partners.
- Accelerate delivery of scalable, production-ready ML solutions.
- Take ML models from prototype to production.
- Optimize code, debug, and perform system integration.
- Manage the end-to-end ML lifecycle, including deployment and monitoring.
- Improve existing codebases.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
