Machine Learning Engineer

Project:

Are you fascinated by machine learning and building robust machine learning pipelines which process massive amounts of data at scale and speed to provide crucial insights to the end consumers?

This is exactly what we, the Machine Learning Engineering group, do.?Our mission is to partner with our Machine Learning Science counterparts to use AI/ML to collaboratively transform our data assets into intelligent and real-time insights to support a variety of applications which are used by 1000+ market managers, analysts, our supply partners, and our travelers.?Our work spans across a variety of datasets and ML models and across a diverse technology stack ranging from Spark, SageMaker, Airflow, DataBricks, Kubernetes, AWS and much more!

Job Description:

Design, develop, debug, and modify components of machine learning and deep learning systems and applications, including data/ETL and feature engineering pipelines. Work collaboratively with data scientists, machine learning engineers, program, and product managers in the development of assigned components

Prototype creative solutions quickly by developing minimum viable products

Ability to write robust code in one or more of Python, Scala, and Java

Proficient in core technologies like Spark, Hadoop, and Hive

Experience in building real-time applications, preferably in Spark and streaming platforms like Kafka and Kinesis.

Good understanding of machine learning pipelines and machine learning frameworks such as TensorFlow and PyTorch

Familiar with cloud services like AWS, Azure, and workflow orchestration tools (e.g., Airflow)

Experienced in using SQL for querying data from relational tables

Key Qualifications:

Degree with strong technical focus (Computer Science, Engineering)
 

Soft Skills:

Excellent analytical and problem-solving skills with an aptitude for troubleshooting issues

Drive for continuous improvement within an agile development team

Communicate and work with geographically distributed cross functional teams