At Integral, we are obsessed with helping web3 businesses streamline financial processes. We partner with the world’s best builders and innovators and enable them to focus on their ultimate goal: building. Traditional financial platforms weren’t forged in the decentralized finance arena. Enter Integral, your game-changer, where bookkeeping and treasury visibility become a seamless sprint, even amidst the labyrinth of crypto intricacies. But here’s the kicker – we’re just getting warmed up.

• —> Coinbase Partners with Integral

• —> Integral Exceeds $100 Billion Accounted for in Under 1 Year

• —> Integral Raised $8.5M to Build Real-Time FinOps Platform for Web3 and Web2 Teams.

We’re 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 you’re eager to work on cutting-edge technologies and contribute to impactful projects, we want to hear from you! We’re searching for highly skilled ML Engineers to join our dynamic team. We’re 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. You’ll 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.

• Fine-tuning: Fine-tuning 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 explainability for the on-chain transactions our customers must later reconcile.

• 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.

• Monitoring: Implementing monitoring solutions to track model performance metrics, detect drift, and trigger re-training to maintain prediction accuracy and reliability.

• Architecture: Improving the state of Integral’s architecture to unlock faster training and deployment cycles, working with the Platform Engineering team.

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

… with the right skillset. 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 early-stage 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 fine-tuning 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.

• Strong communication skills for interacting with both technical and non-technical stakeholders.

$75,000 — $140,000/year