Role Summary

The Senior Associate AI/ML Engineer designs, builds, and deploys production-grade machine learning and multimodal AI solutions that operate across text, image, audio, and video data. The role focuses on transforming unstructured and semi-structured data into scalable AI services that power search, recommendations, automation, analytics, and content intelligence use cases.

This engineer owns model development, pipeline implementation, optimization, and deployment, while contributing to MLOps practices and mentoring junior team members.

Key Responsibilities

Model & Pipeline Development
Build and deploy multimodal ML models across:
Natural Language Processing (NLP)
Computer Vision (CV)
OCR and document understanding
Develop robust pipelines for:
Text processing, entity extraction, and classification
Image tagging, moderation, and visual understanding
Speech-to-text and speaker-level analysis
Implement Retrieval-Augmented Generation (RAG) pipelines with text and multimodal indexing.
Optimization & Performance Engineering
Optimize model inference for latency, throughput,



and cost efficiency across batch and near real-time workloads.
Apply optimization techniques including:
Batching and asynchronous inference
Quantization, pruning, or distillation
GPU and accelerator utilization tuning
Analyze and troubleshoot model performance in production environments.
MLOps, LLMOps & Deployment
Build and maintain CI/CD pipelines for ML workloads using:
GitHub Actions, Azure DevOps, or Jenkins
Deploy models as cloud-native microservices, leveraging:
Docker, Kubernetes (AKS) and FastAPI
Use Azure Machine Learning for:
Experiment tracking
Model registry
Training pipelines and deployment
Implement monitoring and observability for models and pipelines:
Metrics, logging, alerts, and drift detection (e.g., Prometheus, Grafana)
Application & Platform Integration
Integrate AI capabilities into enterprise applications such as:
Search and recommendation systems
Knowledge, docume

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🏢 Happiest Minds Technologies
📍 Pune