We’re looking for an experienced ML Operations Engineer to design, scale, and continuously improve our AWS-based ML platform powering a Contract Intelligence solution.
This role goes beyond traditional MLOps—you will actively contribute to model experimentation, evaluation, and optimization for extracting structured insights from large, complex legal documents.
You will work to improve data extraction accuracy, clause identification, and risk detection, while optimizing processing performance at scale.

Key Responsibilities
ML Engineering & MLOps
Design, deploy, and scale ML pipelines using tools like MLflow, SageMaker, Kubeflow, Airflow, or DVC
Implement CI/CD for ML models including versioning, automated testing, deployment, and rollback
Build and maintain robust training and inference pipelines on AWS
Document AI & NLP Systems
Work on large, dense document processing (contracts, legal documents, scanned files)
Enhance existing OCR and parsing pipelines (already built) to improve accuracy and efficiency
Develop and optimize models for:
Data extraction
Clause extraction




Risk identification
Model Development & Optimization
Fine-tune open-source LLMs and NLP models (LLaMA, Mistral, Falcon, BERT variants)
Continuously update prompts and fine-tune models for better performance
Optimize models for latency, cost, and scalability (quantization, batching, etc.)
Experimentation & Research
Run structured experiments including:
A/B testing
Error analysis
Model benchmarking
Research and evaluate recent open-source models and techniques
Drive improvements in accuracy and processing time through iterative experimentation
Data & Training Strategy
Work with existing training datasets to:
Improve data quality
Build and refine training pipelines
Support client-specific model customization and fine-tuning
Create feedback loops for continuous learning and model improvement
Production & Monitoring
Build scalable pipelines using Lambda, ECS/Fargate, and Step Functions
Implement monitoring

📌 Machine Learning Engineer (Bengaluru)
🏢 Morae
📍 Bengaluru