'OCR' Machine Learning Engineer (Remote) at Fetch Rewards
In order to work at Fetch Rewards candidates must be located in the United States. Thank you!
Who We Are:
We reward shoppers for digitizing their shopping experience.
Our mission is to delight the world’s shoppers with a free smartphone app that is easy, smart and fun.
Why Join the Fetch Family?
We make it better for users even when that's difficult for us
We empower people with information and trust
We challenge ideas, not people
We think bigger and keep building
We find ways to bring the fun to Fetch!
We're committed to building an empowered and inclusive community of innovative and passionate people. As a growing organization, we need team players who can go above and beyond their individual responsibilities to help our company build towards its vision. If you are a creative, hard-working, and fun-seeking person interested in working with a close-knit group of highly talented people, this is the right place for you.
Fetch Rewards is an equal employment opportunity employer.
At Fetch Rewards, our vision is to help people digitize their shopping in a way that is fun and rewarding. Millions of people use our app every month and we are growing rapidly. Headquartered in Madison, WI with offices in Chicago, San Francisco, and New York, we pride ourselves on two things – speed and excellence.
The MLOps team embodies these values and works with a laser focused objective to enable intelligent systems for end users, internal stakeholders, and external partners. We are looking for a OCR Machine Learning Engineer to contribute to this vision and reap the rewards of joining an exciting company in the high growth phase.
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, Spark, Lambda, CloudFormation, Docker, Kinesis, MongoDB, and SageMaker. You’ll also get to join a team of talented individuals 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.You possess:
- Excellent programming skills (we use a lot of Python in this problem space but proficiency in other languages are equally welcome)
- Solid SQL skills
- Experience productionalizing and working with computer vision models
- Knowledge of deployment architectures (on device, off device, etc…)
- Familiarity with Unix systems, shell scripting, and Git
- 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)
- 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
- Bachelor’s degree in Computer Science (or equivalent)
- At least 10 years of relevant full-time work experience
- 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)
- Love of Dogs! . . . Or just tolerance. We're a very canine-friendly workplace