Machine Learning Engineer

We are looking for a Machine Learning Engineer to join our Data Science and Business Intelligence team. Exploiting data is core to our business, and in this role, you will have an opportunity to:

• Enable world-class user experiences across all our products by developing and deploying ML Infrastructure
• Support the organization across a range of areas including experimentation, fraud, market signals, marketing, pricing and many more
• Being responsible for the Machine Learning Infrastructure: feature store, data and model version control system, training pipelines, inference serving, logging, scaling systems, etc.

We are looking for a Machine Learning Engineer who can help to develop ML infrastructure to improve how Blockchain.com operates and how we serve our customers.

Middle

WHAT YOU WILL DO

• Consistently advance the state of ML for your problem, including setting and executing against roadmaps for 6-month+ timeframes. 
• Define projects for other engineers to solve and achieve impact based on your direction. 
• Own the full ML life cycle for a significant new ML product, including its production quality and continued improvements
• Complement our data scientists by contributing to a reliable, secure and maintainable modelling framework that can be used to deploy models to production easily 
• You are a strong advocate for ML excellence 
• Code deliverables in tandem with Data Scientists

WHAT YOU WILL NEED

• Experience with developing end-to-end machine learning pipelines that ensure consistency between development and production environments.
• Ability to design ML architectures for scale with site traffic and complexity of features for predictive algorithms.
• Care with regards to model and data versioning, resource allocation and scaling, and logging to build optimal systems.
• Experience with creating systems that monitor and react to faults in resources, data streams and model responses.

Nice to have

• Experience with Airflow or Google Composer
• Experiences with python and other programming languages such as Java, Kotlin or Scala
• Experience with Spark or other Big Data frameworks
• Experience with Kubernetes for data and ML workloads
• Experience working with open-source machine learning libraries 
• 2-5 years commercial experience in a related role
• Commonly used ML Libraries experience: Xgboost, lgbm, sklearn

 Senior

WHAT YOU WILL DO

• Consistently advance the state of ML for your problem, including setting and executing against roadmaps for 6-month+ timeframes. 
• Define projects for other engineers to solve and achieve impact based on your direction. 
• Own the full ML life cycle for a significant new ML product, including product quality and continued improvements
• You are a strong advocate for ML excellence 
• Code deliverables in tandem with Data Scientists
• Complement our data scientists by providing a reliable, secure and maintainable modelling framework that can be used to deploy models to production easily 
• Play a critical role in helping to set up directions and goals for the team
• Build and ship high-quality code, provide thorough code reviews, testing, monitoring and proactive changes to improve stability
• You are the one who implements the hardest part of the system or feature

WHAT YOU WILL NEED

• Ability to lead/coordinate rollout and releases of major initiatives
• Experience with developing end-to-end machine learning pipelines that ensure consistency between development and production environments.
• Experience working with distributed storage systems
• Ability to design ML architectures for scale with site traffic and complexity of features for predictive algorithms.
• Care with regards to model and data versioning, resource allocation and scaling, and logging to build optimal systems.
• Experience with creating systems that monitor and react to faults in resources, data streams and model responses.
• Experience with MLOps tools for scalable, production-level deployment including past work with feature stores, model hosting and versioning, data versioning, prediction and drift monitoring, and automated remediation

Nice to have

• Experience with Airflow or Google Composer
• Experiences with python and other programming languages such as Java, Kotlin or Scala
• Experience with Spark or other Big Data frameworks
• Experience with Kubernetes Engine
• Experience working with open-source machine learning libraries 
• 5-8 years of commercial experience in a related role 
• Commonly used ML Libraries experience: Xgboost, lgbm, sklearn

 Staff

WHAT YOU WILL DO

• Consistently advance the state of ML for your problem, including setting and executing against roadmaps for 6-month+ timeframes. 
• Complement our data scientists by designing and implementing a reliable, secure and maintainable modelling framework that can be used to deploy models to production easily. 
• Define projects for other engineers to possibly solve and achieve impact based on your direction. 
• Own the full ML life cycle for a significant new ML product, including production quality.
• You are a strong advocate for ML excellence.
• Code deliverables in tandem with Data Scientists.
• Play a critical role in helping to set up directions and goals for the team.
• Build and ship high-quality code, provide thorough code reviews, testing, monitoring and proactive changes to improve stability.
• You are the one who implements the hardest part of the system or feature.

WHAT YOU WILL NEED

• Ability to solve technical problems that few others can do
• Ability to lead/coordinate rollout and releases of major initiatives
• Experience with developing end-to-end machine learning pipelines that ensure consistency between development and production environments.
• Experience working with distributed storage systems
• Ability to design ML architectures for scale with site traffic and complexity of features for predictive algorithms.
• Care with regards to model and data versioning, resource allocation and scaling, and logging to build optimal systems.
• Experience with creating systems that monitor and react to faults in resources, data streams and model responses.
• Deep experience with MLOps tools for scalable, production-level deployment including past work with feature stores, model hosting and versioning, data versioning, prediction and drift monitoring, and automated remediation

Nice to have

• Experience with Airflow or Google Composer
• Experiences with python and other programming languages such as Java, Kotlin or Scala
• Experience with Spark or other Big Data frameworks
• Experience with Kubernetes for data and ML workloads
• Experience working with open-source machine learning libraries 
• 8+ years of commercial experience in a related role 
• Commonly used ML Libraries experience: Xgboost, lgbm, sklearn

• Competitive full-time salary based on experience and meaningful equity in an industry-leading company
• The opportunity to be a key player and build your career at a rapidly expanding, global technology company in an exciting, emerging industry.
• Unlimited vacation policy; work hard and take time when you need it.
• Crypto bonuses
• Performance-based bonuses paid in cash
• Apple equipment provided by the company
• Awesome office locations and remote working options.