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Required Skills & Qualifications
• 6+ years of experience developing and deploying AI/ML solutions.
• Proven track record of end-to-end ownership of AI/ML projects.
• Strong programming skills in Python and SQL.
• Hands-on experience with Generative AI, LLMs, RAG, LangChain, MCP, and orchestration
frameworks.
• Deep understanding of ML algorithms, statistical methods, and embeddings.
• Experience with cloud-native AI/ML workflows (Vertex AI, BigQuery, Dataflow, Cloud
Functions).
• Strong grasp of MLOps pipelines: CI/CD, monitoring, and retraining workflows.
• Demonstrated experience mentoring and guiding junior engineers.
• Knowledge of Docker/Kubernetes for deployment and containerization.
Job ID: 149379541
Skills:
Tensorflow, Pytorch, Cosmos DB, Python, Aws Services, AI ML, Keras, Azure Machine Learning, Anthropic Claude, Agentic AI Platforms, Google AI Platform, Azure OpenAI, Microsoft Copilot, Azure AI Search, Cloud MLOps, CrewAI, LangChain, Generative AI, Semantic Kernel, AutoGPT, AutoGen, GitHub Copilot, AWS SageMaker, Prompt Engineering
Skills:
S3, Pyspark, Microservices, Lambda, Python, Java, Spark SQL, Aws Services, J2EE, Redshift, Git, Databricks, AI Agents, GenAI models, Dataframes, MCP Servers, Data Lake architectures, React UI, LLM Orchestration, Agentic frameworks, Step Functions, MSK, EKS, CI CD pipelines, Athena, OpenAI, Agentic AI libraries
Skills:
hybrid approaches, traditional ML, RAG pipelines, LLMs, retrieval pipelines, context management, document ingestion, prompt orchestration, embeddings, hallucination mitigation, production-grade AI systems
Skills:
API development and integration, Python, Monitoring observability or MLOps concepts, Agentic frameworks or orchestration patterns, Generative AI and LLMs, Tool calling and action execution, CI CD and modern DevOps practices
Skills:
AI Integration Tools - LangChain LlamaIndex, Tensorflow, Pytorch, Machine Learning Frameworks, AI model fine-tuning techniques, Prompt engineering, AWS Bedrock, Vector Database architectures, Advanced Python programming for AI ML applications, Retrieval Augmented Generation RAG, Hugging Face, LoRA Low-Rank Adaptation techniques, Amazon SageMaker, Machine Learning architectures, Generative AI Technologies, AI system design and integration, GraphRAG methodologies, Cloud-native AI solution design, Large Language Models LLMs, AWS AI services, Agentic AI design principles
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