Machine Learning Engineer

London, Miami, San Francisco, Remote

Full Time Senior-level / Expert USD 45K - 150K *
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Blockchain.com

Blockchain.com is the world's most popular way to buy bitcoin, ethereum and more with trust. Securely store, swap, trade and buy the top cryptocurrencies.
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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
COMPENSATION & PERKS
  • 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.
* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net
Job regions: Remote/Anywhere North America
Job countries: United Kingdom United States
Job stats:  9  2  0
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