Artificial Intelligence Engineer
- Posted 2 months ago
- Be among the first 20 applicants
Job Description
Required Experience
• 3+ years of experience as a Data Scientist.
• Strong hands-on skills in Python and ML libraries (e.g., scikit learn, XGBoost).
• Strong experience with agentic frameworks and technologies (e.g. MCP, langchain, Bedrock).
• Experience with large enterprise datasets and analytics platforms (Data Cloud, Snowflake, or similar).
• Experience in measuring the impact of AI products both during R&D and live.
More Info
Key Skills
About Company
Skills:
Large Language Models (LLMs), Nlp, Docker, Flask, Python, Azure DevOps, AWS, Django, Jenkins, Gcp, FastAPI, Azure, Kubernetes, Hugging Face, vector databases, GitLab CI/CD, Pinecone, Azure OpenAI, GitHub Actions, OpenAI APIs, ChromaDB, RAG architectures, LangChain, Generative AI, FAISS, Weaviate, Prompt Engineering, LlamaIndex
Skills:
AI Development Lifecycle (AI DLC, MLops, AWS AI services, Deployment, Monitoring, Continuous Improvement, LLMOps, Gemini models, Copilot Chat, Amazon Bedrock, Amazon Nova, Model evaluation, Amazon Titan, Amazon Q Developer, Anthropic Claude, GitHub Copilot, Prompt engineering
Skills:
software engineering practices , Bash Scripting, Version Control Tools, automation, Git, Computer Vision, Python Programming, Deep Learning, semantic segmentation, YOLO, object detection models
Skills:
Azure Cloud, Tensorflow, Machine Learning, Azure Functions, Pytorch, Python, Nlp, Azure ML, Azure DevOps, FAISS, MLOps tools, MLflow, Kubeflow, Scikit-learn, LLM-based systems, vector databases, Azure ML pipelines, Weaviate, Pinecone, HuggingFace, Spacy, Transformers
Skills:
Sql, AWS, FastAPI, Python, Docker, Multi-Agent Systems, Agent Frameworks, LLM API Integration, OpenSearch, Prompt Engineering, Skill Building, Guardrails, pgvector, RAG Pipelines, Pinecone