Senior Machine Learning Infrastructure Engineer
ESAI SOFTWARE INCORPORATED
New York, NY, United States
3 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Agile Methodology
C++ (Programming Language)
Distributed Systems
Apache Hadoop
Machine Learning
Object-Oriented Software Development
Azure Machine Learning
Data Processing
Apache Spark
Cassandra
Apache Kafka
+1 more
Machine Learning Operations
Job description
Spotify is looking for a Senior Software Engineer to join our team in the Machine Learning space. You will work on building a world class ML platform to address variety of problems such as ads targeting, personalization and pricing. You will work with a team to come up with new and interesting hypotheses, test them, and scale them up to huge data sets with hundreds of billions of data points. Above all, your work will impact the way the world experiences music. WHAT YOU’LL DO
- Design machine learning platforms and pipelines for training and running machine learning models on distributed systems
- Build infrastructure to apply machine learning methods to massive data sets in production environments
- Collaborate with a cross functional agile team of software engineers, data engineers, ML experts, and others to build new product features
- Help drive optimization, testing and tooling to improve data quality
- Determine the feasibility of projects through quick prototyping with respect to performance, quality, time and cost using Agile methodologies
- Work closely with management, research teams, product owners, and fellow team members to develop specifications with clear deliverables to ensure timely completion.
Requirements
- You have development experience with an object-oriented programming language such as C++ or Java
- You have experience implementing machine learning systems at scale
- You have strong experience with data processing and storage frameworks like Hadoop, Scalding, Spark, Storm, Cassandra, Kafka, etc.
- Background in statistics, computational math or machine learning is preferred We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.
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