Machine Learning Engineer

Machine Learning Engineer

This job is no longer open

The Data Platform team works closely with all teams and cross-functional partners (including product, engineering, and data analysts) to build a foundational data stack powering business analytics.

 

We are looking for someone to play a mission-critical role in designing and building the machine models (fraud detection, categorization, recommendation, personalization, price analysis, etc) that powers Bolt. This should be someone with experience, creativity, and passion for producing world-class technology. Companies and consumers alike will rely heavily on what you build, and you’ll have a ton of trust and responsibility. If challenges excite you, and you’re ready for a large one, let us know.

 

Check out our Engineering Blog!

 

Responsibilities

  • Build production ready machine learning models; your models will be the engine that powers all online commerce through Bolt
  • Conduct data analysis to determine which policies we adopt and help inform strategic growth
  • Build machine learning infrastructure, data pipelines and production ready services to serve live traffic
  • Work with other teams at Bolt to engineer new features for models or new product features that help improve Bolt business

Requirements

  • BS in Computer Science, Computer Engineering, or related field
  • 1+ years of experience
  • Thorough understanding of machine learning fundamentals and methodologies
  • Experience building and deploying machine learning models in an applied setting
  • Strong understanding of how to build scalable ML systems supporting online and offline applications
  • Experience working with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Spark ML
  • Familiarity with best practices of lifecycle management for ML models in industry
  • Mastery of a programming language such as Python, Java, Scala

Preferred

  • Masters or PhD in computer science or related field
  • Experience with big data technologies such as BigQuery, Spark, Dataflow, Apache Beam, Pubsub, Cloud Functions, EMR, S3, Glue, Kinesis Firehose, Lambda, etc.
  • Industry experience in e-commerce, financial products, or recommendation systems

Our Stack

  • AWS Lambda for data ingestion and Kinesis Firehose to transport them into S3
  • Step functions and Lambdas to coordinate workflows
  • AWS Redshift as the data warehouse + Spark on EMR for doing ETL
  • Terraform for maintaining infra
  • Jenkins & CircleCI for build pipelines
  • Postgres RDS is our application database
  • Our code base is primarily in Golang & Typescript. However, our data bits are mostly in Python.

 

This job is no longer open
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