Your space-enabled career begins here

At Bolt, we’re all about efficiency - and Machine Learning/AI plays a key role at Bolt to improve user experience and optimizing every part of the product.

As an ML platform engineer, you’ll contribute to the platform used by all Data Scientists and ML Engineers at Bolt to build models and systems for millions of customers - making scalable and reliable ML easy. You’ll get to develop systems combining open-source, cloud, and in-house components and take ML practices at Bolt to the next level!

Your daily adventures will include

• Designing and developing core parts of machine learning infrastructure covering end-to-end ML workflow
• Contributing to our in-house Feature Store Platform serving billions of data points in real-time across all business verticals
• Building value-added services like Data Monitoring, Replay Testing, Load testing components
• Optimizing infrastructure and building automations for optimal resource performance and cost
• Advocating for best software engineering practices and propagating them across stakeholders

Check out Denys (Engineering Manager of the team) speaking about our ML platform at the Nordic Data Science and Machine Learning Days conference: https://www.youtube.com/watch?v=yQmdBHg3j44

We are looking for

• In-depth knowledge of at least one OO programming language. We primarily use Python and Typescript
• 6+ years of experience in software development
• Experience developing end-to-end ML projects and familiarity with MLOPS tooling
• Great communication skills and level of English
• Experience with micro-services and distributed systems for large-scale data processing
• Solid experience with databases (we use TiDB, Redis, Elastic)
• Experience in building ML systems relying on Public Cloud providers (we use AWS)
• A degree in a technical subject (Computer science, Mathematics or similar)

You will get extra credits for

• Experience in building and designing real-time and asynchronous systems
• Familiarity with streaming data technologies for low-latency data processing (Apache Spark/Flink, Apache Kafka, RabbitMQ). A stateful streaming experience will make us excited!
• In-depth knowledge of Docker and Linux, Terraform is a plus
• Experience with NoSQL databases (e.g. Redis, ElasticSearch, Apache Cassandra, ScyllaDB)
• Experience with running large-scale deployments on top of Kubernetes