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Kraken
Senior AI Engineer
at Kraken
16 days ago | 54 views | Be the first one to apply

Senior AI Engineer

Full-time
Europe
Per year
$98,000 To $115,000

About the company

Kraken, the trusted and secure digital asset exchange, is on a mission to accelerate the adoption of cryptocurrency so that you and the rest of the world can achieve financial freedom and inclusion. Our 2,350+ Krakenites are a world-class team ranging from the crypto-curious to industry experts, united by our desire to discover and unlock the potential of crypto and blockchain technology. As a fully remote company, we already have Krakenites in 70+ countries (speaking 50+ languages). We're one of the most diverse organizations on the planet and this remains key to our values. We continue to lead the industry with new product advancements like Kraken NFT, on- and off-chain staking and instant bitcoin transfers via the Lightning Network.

Job Summary

The opportunity

📍Develop AI agents for autonomous task execution and orchestration. 📍Architect systems for intelligent task planning and human-AI collaboration. 📍Design workflows for efficient task routing across AI models and human operators. 📍Build monitoring systems to evaluate agent performance and workflow efficiency. 📍Lead technical initiatives from problem identification to solution implementation. 📍Develop AI/ML pipelines for training, evaluation, and monitoring in production. 📍Partner with SREs and cross-functional teams to optimize AI platform resources. 📍Mentor junior engineers and stay updated on AI/ML trends, driving innovation in the crypto industry.

Skills you should HODL

📍Extensive experience building, fine-tuning, and deploying production-ready ML systems, including LLMs and RAG systems. 📍Strong applied ML fundamentals with expertise in AI algorithms. 📍Proficient in workflow orchestration tools like Prefect, Airflow, or Argo Workflows. 📍Deep experience with post-deployment tasks such as model rollout strategies, performance monitoring, and re-tuning. 📍Expertise in building and deploying web services with container orchestration tools like Kubernetes (K8s). 📍Skilled in ML lifecycle tools like MLFlow, Kubeflow, and inference servers such as Triton, TGI, or vLLM. 📍Proven ability to start projects from scratch and implement CI/CD pipelines using tools like GitLab and ArgoCD. 📍Advanced software engineering skills with a focus on scalable, maintainable, and robust systems.

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