Machine Learning Engineer Apprenticeship

What we’re building and why we’re building it. 

Fetch is a build-first technology company creating a rewards program to power the world. Over the last 5 years we’ve grown from 0 to 18M active users and taken over the rewards game in the US with our free app. The foundation has been laid. In the next 5 years we will become a global platform that completely transforms how people connect with brands. 

It all comes down to two core beliefs. First, that people deserve to be rewarded when they create value. If a third party directly benefits from an action you take or data you provide, you should be rewarded for it. And not just the “you get to use our product!” cop-out. We’re talkin’ real, explicit value. Fetch points, perhaps. 

Second, we believe brands need a better and more direct connection with what matters most to them: their customers. Brands need to understand what people are doing, and have a direct line to be able to do something about it. Not just advertise, but ACT. Sounds nice, right? 

That’s why we’re building the world’s rewards platform. A closed-loop, standardized rewards layer across all consumer behavior that will lead to happier shoppers and stronger brands.

Fetch Rewards is an equal employment opportunity employer.

The Role:

The ML Engineering team embodies these values and works with a laser-focus on enabling intelligent systems for end users, internal stakeholders and external partners. We are looking for a Machine Learning Engineer Apprentice to contribute to this vision and reap the rewards of joining an exciting company in the high growth phase.

Apprentices are paid, and hired with the intention of conversion to a full time role after 6 - 12 weeks of excellent performance. Apprentices are paired 1:1 with a Machine Learning Engineer for personalized mentorship on a project in the machine learning engineering domain, and additionally work cross-functionally with Data Scientists, Data Engineers, and more.

Your focus will be on developing pipeline frameworks, micro-services, and infrastructure solutions that can scale to match the company’s growth trajectory. We don't lock ourselves into particular technologies, but some we are currently using include AWS, Snowflake, Python, Lambda, CloudFormation, AWS CDK, Docker, Kinesis, Redis and SageMaker. You’ll get to join a team of talented engineers who will provide you with hands-on mentorship on topics ranging from software development to DevOps to analytics. Success in this role requires the ability to analyze challenging problems, propose solutions under the guidance of experienced teammates, and implement designs within timeframes that keep up with business needs.

The ideal candidate:

• Excellent programming skills (we use a lot of Python in this problem space but proficiency in other languages are equally welcome)
• Solid SQL skills
• Familiarity with Unix systems, shell scripting, and Git
• Interest in building and experimenting with different tools and tech, and sharing your learnings with the broader organization
• The desire to work with other teams in the organization (e.g., Data Science, Software Development, DevOps) to build tools and solutions that enable the training and deployment of machine learning enabled services within the Fetch ecosystem
• Experience developing solutions on cloud services or infrastructure (we’re 100% AWS)
• Experience with relational (SQL), non-relational (NoSQL), and/or object data stores (some technologies we use include Snowflake, MongoDB, S3, HDFS, Postgres, Redis, DynamoDB)
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Bonus Points For:
  • Excellent written and verbal communication skills
  • Familiarity with open source software and dependency management
  • Machine learning development and/or data science experience
  • Cloud engineering and DevOps skills (e.g., AWS, CloudFormation, Docker)
  • ETL process, data pipeline, and/or microservice development experience
  • Familiarity with messaging and asynchronous technologies (e.g., SQS, Kinesis, RabbitMQ, Kafka)
  • Big data development skills (e.g., Spark, Hadoop, MPP DW)