ML Engineer - Remote

This is a remote position.

At our client we are obsessed with helping web3 businesses streamline financial processes. We partner with the worlds best builders and innovators and enable them to focus on their ultimate goal: building. Traditional financial platforms werent forged in the decentralized finance arena. Enter our client your gamechanger where bookkeeping and treasury visibility become a seamless sprint even amidst the labyrinth of crypto intricacies. But heres the kicker were just getting warmed up.

Were looking for the right person

Are you a passionate and skilled engineer with a knack for building robust and scalable applications Do you thrive in a collaborative environment ready to contribute your expertise to revolutionize the fintech industry If youre eager to work on cuttingedge technologies and contribute to impactful projects we want to hear from you!

Were searching for highly skilled ML Engineers to join our dynamic team. Were looking for someone who can bring their expertise in building AI products scoped to finance and crypto use cases architecting an initial pipeline (with support from our infra team) and ultimately ship AI features that delight our customers. Youll spend your time on the following:

Development: Design develop and deploy machine learning models for various applications within the crypto finance domain such as predictive analytics fraud detection transaction classification and risk management.

Finetuning: Finetuning ML models for specific use cases such as developing heuristics that detect fraudulent transactions enhance reconciliation processes by analyzing historical transaction data and provide greater explain ability for the onchain transactions our customers must later reconcile.

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Deployment: Automating the deployment of ML models to production environments using tools and frameworks like Docker Kubernetes and CI/CD pipelines ensuring high availability low latency and accuracy.

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Monitoring: Implementing monitoring solutions to track model performance metrics detect drift and trigger retraining to maintain prediction accuracy and reliability.

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Architecture: Improving the state of our client architecture to unlock faster training and deployment cycles working with the Platform Engineering team.

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Collaboration: Collaborating with the fullstack engineering team to ensure seamless integration of ETL processes data warehousing and streaming to facilitate efficient model training and evaluation.

Requirements

• 5 years working on production web applications
  
• Keen interest in working in crypto and building finance products
  
• Built and deployed ML models into production
  
• Ability to operate in an earlystage startup where much of the ML and data science infra is being built from scratch
  

Key Skills

• Expertise in at least one ML framework (e.g. TensorFlow PyTorch) and experienced with orchestration tools (Airflow Docker Kubernetes)
  
• Experience with model finetuning and heuristic development.
  
• Strong knowledge of building and maintaining processing pipeline using tools like Apache Spark Airflow or Kafka.
  
• Expertise in deploying machine learning models to production environments.
  
• Familiarity with monitoring and ensuring the performance of deployed models.
  
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  Strong communication skills for interacting with both technical and nontechnical stake
  

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