AI ML Architect

Infovision Labs; Pune District, Bengaluru; Hybrid; INR 1,800,000 - 3,400,000; Full time

Job summary

Infovision Labs seeks a highly experienced ML/AI Architect to design, build, and scale enterprise-grade AI solutions in Pune. You will lead ML system architecture, GenAI design, and MLOps automation, delivering production-ready AI at scale.

The role requires strong leadership, cloud-native data engineering expertise, and collaboration with cross-functional teams to drive innovation and best practices across the organization.

Qualifications

• Proven expertise in building end-to-end ML/AI systems.
• Experience with LLMs, GenAI, and embeddings.
• Strong background in MLOps, CI/CD, and cloud-native data engineering.
• Hands-on with PyTorch/TensorFlow and Transformers.

Responsibilities

• Architect end-to-end ML systems, from data ingestion to monitoring.
• Design scalable ML pipelines for classical ML, DL, and GenAI workloads.
• Lead deployment using Kubernetes, Docker, Terraform, and GPU stacks.
• Mentor ML/AI teams and drive enterprise-grade AI solutions.

Skills

LLMs / GenAI knowledge

ML / DL techniques

MLOps & CI/CD

Data Engineering

Cloud platforms

Kubernetes & Docker

Vector databases

Model evaluation & explainability

Monitoring & security

Leadership & mentoring

Tools

PyTorch

TensorFlow

Transformers

Kubeflow

SageMaker

Vertex AI

Azure ML

PySpark

SQL

Airflow

MLflow

Weaviate

Pinecone

Chroma

Milvus

Job description

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 GenAI 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 LoRA/QLoRA 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 GenAI solutions within our Digital Transformation Practice. The role requires strong 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 / GenAI: GPT-4/5, Llama 3/3.5, Qwen, Claude, RAG, prompt engineering, LoRA/QLoRA, embeddings
• ML / DL: PyTorch, TensorFlow, Transformers, CNNs, XGBoost, NLP/NLU, NER
• MLOps: MLflow, Airflow, Kubeflow, SageMaker, Vertex AI, Azure ML, CI/CD/CT, monitoring
• Data Engineering: PySpark, SQL, ETL/ELT pipelines, orchestration, data quality
• Cloud & DevOps: AWS, Azure, GCP, Kubernetes, Docker, Terraform, GPU stack
• Other: Vector DBs (Pinecone, Weaviate, Chroma, Milvus), observability, model optimization, model explainability (SHAP/LIME)