Unlock the Power of Generative AI: Software Development Career Opportunity

14 hours ago

Shimoga, Karnataka, India beBeeDeveloper Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Generative AI Development Opportunity

Are you a skilled developer looking to leverage your expertise in Generative AI and Large Language Models (LLMs)? We have an exciting opportunity for you to join our team as a Generative AI Engineer.

  • Fine-tune and optimize LLMs for domain-specific tasks using frameworks such as LangChain, LlamaIndex, or similar.
  • Integrate LLMs with APIs, databases, vector stores, and enterprise applications to build modular AI applications.
  • Evaluate and implement model deployment strategies in various environments, including on-prem, cloud, serverless, or containerized.
  • Collaborate with cross-functional teams to deliver end-to-end AI solutions that meet business objectives.
  • Stay up-to-date with the latest advancements in AI, ML, and GenAI research and propose adoption of new technologies.
  • Implement MLOps best practices for continuous training, deployment, and monitoring of models in production.
  • Ensure responsible AI practices by focusing on bias mitigation, data privacy, and compliance.
Requirements
  • 5+ years of experience in software development, preferably in Python; familiarity with Java, C#, or Node.js is a plus.
  • 2+ years of hands-on experience in Generative AI and LLM-based development.
  • Strong knowledge of AI/ML fundamentals, including NLP, deep learning, embeddings, and transformers.
  • Experience with LLMs, such as OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral, or similar.
  • Proven track record of delivering at least 2 production-grade LLM-based projects.
  • Experience with LangChain, LlamaIndex, Haystack, or similar frameworks.
  • Familiarity with vector databases, such as Pinecone, Weaviate, Milvus, FAISS, Chroma.
  • Hands-on experience with cloud platforms, such as AWS, Azure, GCP, and AI services like Bedrock, VertexAI, Azure OpenAI.
  • Proficiency in containerization and deployment tools, including Docker, Kubernetes, and CI/CD pipelines.
  • Experience with MLOps tools, such as MLflow, Kubeflow, Weights & Biases, for model lifecycle management.
  • Strong problem-solving, analytical, and communication skills.

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