Technical Lead - AIML
Dotsquares
- Location
- Jaipur, Rajasthan, India
- Job type
- Full-time
Required skills
- LangChain
- Python
- AWS
- Azure
- backend
- computer vision
- deep learning
- Django
- Docker
- FastAPI
- Flask
- GCP
- Kafka
- Kubernetes
- machine learning
- NLP
- PostgreSQL
- predictive analytics
- Redis
- TensorFlow
- Pytorch
- REST APIs
About the role
Dotsquares
Website:
dotsquares.com
Job details:
Tech Lead – AI/ML
Key Responsibilities
- Design scalable, production-ready AI/ML architectures for enterprise applications.
- Lead solutions across Machine Learning, Deep Learning, Generative AI, LLMs, RAG, Agentic AI, NLP, Computer Vision, Speech AI, and Predictive Analytics.
- Architect and implement LLM applications using OpenAI, Claude, Gemini, Llama, Qwen, Mistral, etc.
- Design advanced RAG pipelines, vector search, embeddings, reranking, grounding, evaluation, guardrails, and observability.
- Build AI agents and multi-agent workflows using LangGraph, LangChain, AutoGen, CrewAI, Copilot Studio, etc.
- Lead ML model development, optimization, deployment, and evaluation using PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
- Design AI infrastructure across AWS/Azure/GCP, including Docker, Kubernetes, GPUs, model serving, CI/CD, and MLOps.
- Lead and mentor AI/ML engineers, conduct architecture/code reviews, and drive technical decisions.
- Work directly with clients on discovery, solution architecture, POCs, technical proposals, consulting, and pre-sales.
- Evaluate emerging AI technologies and drive innovation from POC to production.
Required Skills
- Strong Python, Machine Learning, Deep Learning, NLP and/or Computer Vision expertise.
- Strong experience with LLMs, Generative AI, RAG, Prompt Engineering, Embeddings, Vector Databases, Tool/Function Calling, and LLM Evaluation.
- Experience building AI agents and agentic workflows.
- Strong backend development experience with FastAPI, Flask, Django, or equivalent.
- Good knowledge of REST APIs, PostgreSQL/MongoDB, Redis/Kafka or similar technologies.
- Experience with AWS/Azure/GCP, Docker, CI/CD, MLOps, Kubernetes and GPU-based deployments.
- Strong technical leadership, problem-solving, communication, mentoring, and client-facing skills.
Preferred
- Experience taking AI products from POC → Production.
- Enterprise GenAI and multi-agent system experience.
- LLM inference/GPU optimization and open-source LLM experience.
- Multimodal AI and RAG evaluation experience.
- International client consulting and pre-sales experience.
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