Experience: 8 to 14 Years
Location: Bangalore, Pune
Immediate joiners
Job Details
Roles & Responsibilities
Architect end-to-end ML systems covering data ingestion, feature engineering, model training, deployment, and monitoring.
Design scalable ML pipelines for classical ML, deep learning, and Gen AI workloads including LLMs, RAG, embeddings, and semantic search.
Select optimal algorithms, frameworks, and cloud platforms to address complex business and technical challenges.
Implement model optimization strategies such as quantization, pruning, distillation, and Lo RA/QLo RA fine-tuning.
Build LLM-powered solutions using prompt engineering, knowledge grounding, agents, and retrieval-augmented generation.
Work with top LLMs (GPT-4/5, Llama 3/3.5, Qwen, Claude, Gemini) and integrate vector DBs like Pinecone, Weaviate, Chroma, Milvus.
Evaluate and improve LLM and ML model performance, reduce hallucinations, and ensure security and compliance.
Lead development of ML, NLP, NER, and deep learning models using Transformers, CNNs, XGBoost, and other advanced architectures.
Drive data science workflows including EDA, feature engineering, statistical modeling, and explainability (SHAP/LIME).
Architect MLOps pipelines (CI/CD/CT), enabling model versioning, monitoring, drift detection, and automated retraining.
Deploy models at scale using Kubernetes, Docker,



Terraform, serverless components, and GPU-based environments with strong observability.
Collaborate with cross-functional teams, lead technical discussions and POCs, and mentor ML/AI teams to deliver enterprise-grade solutions.
Job Description
We are seeking a highly experienced ML/AI Architect to design, build, and scale enterprise-grade AI/ML and Gen AI solutions within our Digital Transformation Practice. The role requires solid technical leadership across ML system architecture, LLM-based solution design, MLOps automation, and cloud-native data engineering. The ideal candidate will drive innovation, establish best practices, and deliver production-ready AI solutions at scale
Key Skills & Competencies
LLMs / Gen AI: GPT-4/5, Llama 3/3.5, Qwen, Claude, RAG, prompt engineering, Lo RA/QLo RA, embeddings
ML / DL: Py Torch, Tensor Flow, Transformers, CNNs, XGBoost, NLP/NLU, NER
MLOps: MLflow, Airflow, Kubeflow, Sage Maker, Vertex AI, Azure ML, CI/CD/CT, monitoring
Data Engineering: Py Spark, SQL, ETL/ELT pipelines, orchestration, data quality
Cloud & Dev Ops: AWS, Azure, GCP, Kubernetes, Docker, Terraform, GPU stack
Other: Vector DBs (Pinecone, Weaviate, Chroma, Milvus), observability, model optimization, model explainability (SHAP/LIME)

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