Description

Description:

 

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.

 

 

Details:

Please provide 2-3 values or traits that are important to this role 
1. **Collaboration:** The ability to work well in a team and communicate effectively with colleagues.
2. **Problem-solving:** Strong analytical and creative problem-solving skills.
3. **Adaptability:** Willingness to learn and adapt to new technologies and methodologies.
Please list 3-4 functional activities the resource should be capable of 
1. **Software Development:** Proficient in designing, coding, testing, and debugging software applications.
2. **System Architecture:** Capable of contributing to the design and architecture of complex software systems.
3. **Code Review and Optimization:** Skilled in reviewing code, providing constructive feedback, and optimizing for performance.
4. **Collaborative Problem Solving:** Ability to work with cross-functional teams to address technical challenges.
What technical skills will successful candidates possess? 
Please check job description for tech skills
Tell us about your team 
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.
Is there any industry specific experience that would separate one candidate from another? 
Experience in Java, python and handling highly scalable systems would be beneficial, having a database with knowledge of SQL,NO SQL and spark is a plus. We manage service and deployments dodging and building high performance components with strong foundation in software engineering is recommended

Key Skills
Education

Any Graduate

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