Futran Tech Solutions
Senior AIML Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Pune, Maharashtra, India
Work mode:
Onsite
Published on:
11 September 2026
What they need
Job Title - AI/ML Engineer
Location - Pune, Baner
Work Mode - 5 days wfo
Shift - UK Shift - 1pm to 10pm
Job Description:
Core Experience Required
Strong experience with RAG-based systems or Graph-based architectures
Minimum 5 years of AI/ML experience
Experience with MCP
Prior work on end-to-end AI system development AI System Development
Design and build production AI/ML systems, including agentic workflows, multi model pipelines, and intelligent automation
Develop and optimize LLM-based applications using prompt engineering, RAG, and fine-tuning techniques
Build AI agent frameworks that orchestrate complex reasoning, tool usage, and multi-step workflows ML Engineering & MLOps
Train, evaluate, and deploy ML models across classification, NLP, recommendation, and generative use cases
Implement MLOps pipelines for model versioning, monitoring, A/B testing, and continuous improvement
Optimize model performance, latency, and cost in production environments Data & Infrastructure
Design vector databases, embedding systems, and semantic search architectures
Build scalable data pipelines for training, inference, and continuous learning
Create evaluation frameworks to measure AI system quality, safety, and performance Technical & Engineering Skills
Strong programming skills in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
Hands-on experience with LLMs (GPT, Claude, Llama, etc.) and a clear understanding of their capabilities and limitations
Proficiency with frameworks/tools such as LangChain, LlamaIndex, DSPy, Hugging Face, OpenAI API, Anthropic API
Strong fundamentals in data structures, algorithms, and system design
Experience building APIs, microservices, and distributed systems (FastAPI, Node.js, etc.)
Cloud experience on AWS, GCP, or Azure, along with Docker and Kubernetes
Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB, Qdrant, and SQL/NoSQL databases
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