AI Developer
2 weeks ago
Location: Kochi, Kerala
Department: AI & Data Science
Employment Type: Full-Time
About the Role:
We are looking for an experienced Python AI Developer with 4–7 years of hands-on experience in real-world AI/ML solutions. You will be responsible for building, deploying, and maintaining scalable AI systems in production, with a focus on Machine Learning, Deep Learning, LLMs, Agents, and NLP. This role demands strong software engineering fundamentals, practical deployment experience, and a deep understanding of both classical and modern AI approaches.
Key Responsibilities:
Build, fine-tune, and deploy Large Language Models (LLMs) and AI agents for real-world use cases (e.g., chatbots, summarization, RAG systems, recommendation engines).
Develop and deploy production-grade models with CI/CD pipelines, monitoring, logging, and rollback strategies.
Integrate AI systems with SQL/NoSQL databases (e.g., PostgreSQL, MongoDB, Redis).
Use cloud services (AWS or Azure) for model training, deployment (e.g., SageMaker, Azure ML), and orchestration (e.g., Lambda, Functions, Batch).
Collaborate with cross-functional teams including Data Engineers, Product Managers, and DevOps to ensure scalable and maintainable solutions.
Conduct performance tuning, A/B testing, and continuous optimization of deployed models.
Stay up to date with the latest AI research and apply relevant advancements to existing products.
Required Skills & Experience:
4–7 years of experience in Python programming, with a focus on AI/ML systems.
Proven experience in deploying AI models in production, not just building POCs.
Expertise in Machine Learning, Deep Learning, and Natural Language Processing (NLP).
Strong hands-on experience with LLMs (OpenAI, Claude, Mistral, LLaMA, etc.) and agentic workflows.
Experience with model serving tools like FastAPI, Django, Flask, Docker, Kubernetes etc.
Familiarity with SQL/NoSQL databases: PostgreSQL, MongoDB, Redis, or DynamoDB.
Experience with Vector Databases (e.g., FAISS, Pinecone, Weaviate).
Solid understanding of cloud services: AWS (SageMaker, Lambda, S3, ECS) or Azure (Azure ML, Blob Storage, Functions).
Experience working with APIs, microservices, and distributed systems.
Nice to Have:
Exposure to RAG (Retrieval Augmented Generation) or multi-agent orchestration frameworks like LangChain or Haystack.
Knowledge of data privacy, security, and compliance in ML systems.
Contributions to open-source AI/ML projects or research publications.
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