Artificial Intelligence Engineer For Mumbai only

Role & responsibilities

Location: Mumbai only

Experience: 6+ years

Interview process 3 rounds of interview

Employment Type: Full-time

Notice Period: Immediate to 30 days only

• Design, build, and fine-tune machine learning, deep learning, and Generative AI models for real-world use cases.
• Develop Agentic AI systems using frameworks such as ADK, LangGraph, or equivalent for orchestration and reasoning.
• Build solutions leveraging LLMs, RAG pipelines, embeddings, and vector databases.
• Design and implement AI systems for text, structured/unstructured data, and conversational use cases.
• Apply core NLP techniques including classification, summarization, entity recognition, and semantic search.
• Develop scalable algorithms for search, retrieval, and real-time inference.
• Build and integrate AI microservices into enterprise systems using APIs, event-driven architectures, and cloud services.
• Deploy and operate AI workloads using Docker, Kubernetes, and managed cloud AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI).
• Optimize solutions for performance, cost, latency, and security.
• Collect, preprocess, and manage large datasets for fine-tuning and inference.
• Continuously monitor and optimize models and prompts for accuracy, scalability, and efficiency.
• Partner with Solution Architects and business teams to translate requirements into production-ready AI solutions.
• Champion Responsible AI practices, including fairness, bias mitigation, and compliance.

Required Skills

• Proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch).
• Strong understanding of Generative AI concepts (transformers, embeddings, fine-tuning).
• Experience with Agentic AI frameworks (ADK, LangGraph, AutoGen).
• Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment.
• Knowledge of prompt engineering, vector databases (Pinecone, Weaviate), and retrieval-augmented generation (RAG).
• Hands-on with cloud-native AI deployments (Azure, AWS, GCP).
• Familiarity with API-driven design, microservices, and event-driven architectures.

Qualifications

• Bachelors/Masters in Computer Science, AI, Data Science, or related field.
• Hands-on experience in AI/ML development and deployment.
• Hands-on experience with LLMs and Generative AI applications.

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