AI Solutions Developer

2 days ago

Tiruppur, Tamil Nadu, India beBeeArtificial Full time ₹ 15,00,000 - ₹ 24,00,000
Job Description

As a Generative AI Engineer, you will design and develop AI/ML solutions with a focus on Generative AI and Large Language Models. Your expertise in fine-tuning, prompt-engineering, and optimizing LLMs for domain-specific tasks will be crucial in building modular AI applications.

Key Responsibilities:

  1. Design and develop AI/ML solutions using frameworks such as LangChain or similar.
  2. Integrate LLMs with APIs, databases, vector stores, and enterprise applications.
  3. Evaluate and implement model deployment strategies across various environments.
  4. Work closely with cross-functional teams to deliver end-to-end AI solutions that meet business requirements.
  5. Stay updated with the latest advancements in AI, ML, and GenAI research.
  6. Implement MLOps best practices for continuous training, deployment, and monitoring of models in production.
  7. Mitigate bias, ensure data privacy, and adhere to compliance standards.

Required Skills and Qualifications

  • 5+ years of experience in software development, preferably with Python.
  • 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.
  • A proven track record of delivering at least 2 production-grade LLM-based projects.
  • Framework Familiarity: Experience with LangChain, LlamaIndex, Haystack, or similar frameworks.
  • Vector Databases: Familiarity with vector databases, such as Pinecone, Weaviate, Milvus, FAISS, Chroma.
  • Cloud Platforms: Hands-on experience with cloud platforms, including AWS, Azure, GCP, and AI services like Bedrock, VertexAI, Azure OpenAI.
  • Containerization and Deployment Tools: Proficiency in containerization and deployment tools, such as Docker, Kubernetes, CI/CD pipelines.
  • MLOps Tools: Experience with MLOps tools, such as MLflow, Kubeflow, Weights & Biases, for model lifecycle management.

What We Offer

  • A dynamic and collaborative work environment.
  • Ongoing training and professional development opportunities.
  • A competitive salary and benefits package.

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