Senior Machine Learning Engineer

Requirements

This is a W2 engagement. The pay rate reflects the fact that this is a W2 engagement.

What You’ll Be Working On

Our team manages the platform for AI ML teams in Expedia. The Feature lifecycle team specifically works on managing feature stores for the models. We provide low latency services for model inferencing use cases. Support regular feature refresh pipelines and data for batch inference and training use cases.

We're looking for a Sr ML Engineer to join our team.

Key Activities

• Software Development: Proficient in designing, coding, testing, and debugging software applications.
• System Architecture: Capable of contributing to the design and architecture of complex software systems.
• Code Review and Optimization: Skilled in reviewing code, providing constructive feedback, and optimizing for performance.
• Collaborative Problem Solving: Ability to work with cross-functional teams to address technical challenges.

Key Requirements

• Ability to write robust code in one or more of Python, Go, 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. (good to have)
• Familiar with cloud services like AWS, Azure, and workflow orchestration tools (e.g., Airflow).
• Degree with a strong technical focus (Computer Science, Engineering).
• 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.
• Actively participate in group technology reviews to critique work of self and others.