Senior Machine Learning Engineer

3 weeks ago

Bengaluru, India Expedia Group Full time
Senior Machine Learning Engineer

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 in Expedia, do.

Our mission is to partner with our Machine Learning Science counterparts to use AI/ML to collaboratively transform Expedia’s 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, Airflow, Databricks, Kubernetes, AWS and much more

What you’ll do:Work in a cross-functional team of Machine Learning engineers and Data scientists to lead the design and development of large scale batch and real-time ML Services

Design, implement and deploy large scale data pipelines (both real time and batch) and back-end services

Lead the end-to-end product life cycle for mid to large machine learning/data engineering projects: Design, development, model validation/testing, model deployment, and providing operational excellence and support

Find and advocate for Industry standards and best practices in machine learning engineering methodologies, techniques, and technologies

Contribute to advancing the team's design methodology and quality programming practices and mentor junior team members to adapt best practices

Innovate and implement new ideas to solve complex software problems and prototype creative solutions to enable product MVP's

Independently understand scheduling, cost constraints, and impact to other teams; and make resource and architectural trade-offs based on those factors

Anticipate and prevent problems and roadblocks, before they occur, and present technical issues and their impact to leadership

Lead, coordinate, and collaborate on multiple concurrent and complex cross-organizational initiatives

Effectively build and maintain a network of key contacts across company, and leverage these contacts to achieve results

Communicate and work effectively with geographically distributed cross functional teamsDrive for continuous improvement in software and development process within an agile development team

Who you are:Bachelor's or Master's Degree in software engineering, computer science, informatics or in a related technical field; or equivalent related professional experience

8 to 10+ years of work experience in software engineering

4+ years experience in designing and implementing BigData/ML applications (data ingestion, real-time data processing and batch analytics) in Spark Streaming, Kafka, Hadoop

Experience on Hadoop-ecosystem technologies in particular MapReduce, Spark, Hive, YARN

Experience in productionizing machine learning models including feature engineering, model scalability, model validation, and model deployment

Solid server-side programming skills in multiple languages (Scala/Java and Python), and hands-on experience in OOAD, design patterns, NoSQL and SQL

Strong experience with cloud computing platforms (AWS, EMR, Kubernetes, Docker)

Strong experience working with ML platforms (Databricks, SageMaker, etc.)

Solid knowledge in SQL (T-SQL/PL-SQL), ETL and data modelling

Experience with microservice architecture, and design

Experience on machine learning toolkits like spark mllib, H20, scikit-learn, R and ML techniques

Strong command with machine learning libraries such as PyTorch and Tensorflow and knowledge of common integration patterns for serving inference with them

Familiar with training models with very large datasets- strategies for parallelizing and optimizing the training jobs especially with GPUs or large-compute

You have hands-on experience with workflow management tools (e.g. Airflow)

Familiar with machine learning inference at scale. Can instrument streaming or parallel inference tasks to accommodate large traffic or volume of data

Experience working with Agile/Scrum methodologies

Experience on Recommender Systems is a plus.

Familiarity with the e-commerce or travel industry

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