Machine Learning Engineer - Chainbased Limited : Job Details

We're looking for a seasoned Machine Learning Engineer who understands the full life cycle of training machine learning models and putting them into production. This person can help us build, expand, and maintain our machine learning infrastructure and ecosystem.

Engineering – Software Engineering / Full Time / Remote

About the Opportunity

We're looking for a seasoned Machine Learning Engineer who understands the full life cycle of training machine learning models and putting them into production. This person can help us build, expand, and maintain our machine learning infrastructure and ecosystem.

In this role, you'll be a part of the Data team. You'll help implement machine learning systems that have significant impact on critical functions of the business. You'll collaborate closely with data scientists and operate cross-functionally with Engineering, Ops, Product, Fraud Prevention, and more.

As an ML Engineer, you will assess current ML design, strategize to improve and expand ML implementations, and ensure system effectiveness.

This role will be hybrid, requiring some time in our office in designated locations.

What you will do

About You

You have experience working closely with data scientists to bring models to production, understand implementing ML systems reliably, and are familiar with cloud infrastructure. You're eager for a challenge and want to impact Chainbased's success by scaling its ML capabilities.

Requirements

• Experience in productionising ML systems is essential.
• Experience training ML models is highly desirable.
• Proficiency in Python and SQL.
• Knowledge of Terraform, Terragrunt for IaC.
• Hands-on with real-time systems like Kafka, Kafkaconnect, Redpanda, Pub/Sub.
• Experience with Kubernetes, Docker, deployment strategies (canary, blue-green).
• Experience with CI/CD tools like CircleCI, Drone, Github Actions, ArgoCD.
• Knowledge of Big Data tools like Spark, Dataflow, Flink.
• System design skills considering performance and trade-offs.
• Applying software engineering practices to ML, including CI/CD, unit testing, automation.
• Experience with MLOps tools such as KubeFlow, DVC, MLFlow.
• Cloud provider experience (GCP, AWS, Azure), with GCP preferred.
• Interest or experience in FinTech, crypto, or web3 is a plus.

Core Principles

Embodies Chainbased's “BLOCK Values”: O - Own It, C - Crypto Curious.

Perks

• Equity package
• Unlimited holidays
• Paid parental leave
• Home office setup allowance
• Monthly product budget
• Work in a disruptive, fast-growing industry