Role overview
- Programming & Data Engineering: o Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex. o Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools. o Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval. o Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing. • Deployment & MLOps: o Critical: Hands-on experience deploying GenAI-based models to production environments. o Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines. o Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments. • Cloud & Containerization: o Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment. • Soft Skills: o Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Ai Engineer Mlops Pytorch Tensorflow Data Engineer Generative Ai