ML Software Engineer

Job Description

The Client is looking for a Machine Learning Engineer to build the ML platform which provides robust infrastructure to transform models into products for 145,000+ customers. The ideal candidate will have experience as a software engineer or MLOps Engineer, a desire to work in ML/AI domain and a deep interest in developing complex systems and automating the simple ones.

Responsibilities

• Build software to move machine learning from experiment to production
• Collaborate closely with fellow Engineers to find innovative solutions to technical challenges
• Contribute to initiatives around improving the scalability and robustness of platforms
• Prototype, and refine scalable infrastructure
• Build really cool products with a great team

Qualifications

Basic Qualifications:

• At least 2 years building scalable and stable software applications
• Proficiency in at least one of core languages: Python or Java
• Exposure to AWS infrastructure
• A self-managed and dedicated approach with the ability to work independently

Preferred Qualifications:

• Experience or knowledge of Docker and Kubernetes
• Experience building and deploying machine learning models
• Strong understanding of end-to-end machine learning pipelines and components
• Familiarity with data engineering tools. E.g. Spark
• Familiarity with AI/ML workflows and associated tooling. E.g. Sagemaker, ML Flow, Metaflow
• Experience or knowledge of Infrastructure as Code tools (e.g. Terraform)

Tech Stack

• Code is written in Python, Java, Scala and Go
• Servers live in AWS
• Team manages infrastructure using AWS CloudFormation, Terraform
• Data is stored in S3, RDS MySQL, Redis, ElasticSearch, and Aurora and streamed through Kafka
• Services are deployed to Kubernetes using Docker