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.
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.
Strong Python programming expertise, emphasizing clean, efficient code.
Demonstrated ability to solve complex challenges using effective abstractions and best practices.
Strong communication skills to articulate complex ideas to both technical and non-technical audiences.
Familiarity with agent frameworks such as Autogen and LangChain is highly desirable.
Yearly based
Worldwide
United States
