Senior Machine Learning & AI Engineer Job at Cogniter Technologies (Chandigarh)

Job Description

Cogniter Technologies is seeking a highly skilled Senior Machine Learning & AI Engineer to design, develop, and deploy scalable, production-ready AI solutions. This role focuses primarily on classical machine learning, deep learning, robust dataset engineering, and enterprise-grade deployment practices. Generative AI and agentic frameworks will be leveraged selectively—only where they provide clear, measurable business value. The ideal candidate possesses strong ML fundamentals, hands-on experience across the complete AI lifecycle, and the capability to take models from raw data preparation to reliable, monitored production systems.

Job Responsibility

Design, train, and optimize machine learning and deep learning models for structured and unstructured data
Build end-to-end ML pipelines including data ingestion, preprocessing, feature engineering, training, validation, and testing
Apply supervised, unsupervised, and semi-supervised learning techniques
Evaluate models using metrics such as precision, recall, F1-score, ROC-AUC, and other performance indicators
Perform hyperparameter tuning to improve accuracy, robustness, and generalization
Create, clean, augment, and manage large-scale datasets
Design synthetic or semi-synthetic data pipelines when labeled datasets are limited
Ensure data integrity, quality control, and proper dataset versioning
Collaborate with data teams to build efficient ETL and feature engineering pipelines
Develop and fine-tune deep learning models using PyTorch or TensorFlow
Build NLP pipelines for tasks such as classification, semantic search, information extraction, and retrieval
Optimize neural networks using regularization, pruning, quantization, and transfer learning
Develop Python-based APIs using FastAPI or Flask
Implement batch and real-time inference pipelines
Optimize inference services for low latency, scalability, and fault tolerance
Integrate AI services into existing enterprise applications
Containerize ML applications using Docker
Deploy models in production with appropriate compute and memory allocation
Implement scalable inference services using load-balancing strategies
Monitor model performance, data drift, and inference latency
Manage model versioning, rollback mechanisms, and lifecycle governance
Apply LLMs and Generative AI solutions only where they provide measurable business impact
Implement Retrieval-Augmented Generation (RAG) pipelines when appropriate
Use agentic frameworks such as LangChain or LangGraph selectively
Ensure output reliability, factual grounding, and controlled responses
Work closely with product, backend, and data teams to translate business needs into robust ML systems
Contribute to system architecture discussions and technical planning
Stay updated with advancements in machine learning research and production system design

Requirements

3+ years of hands-on experience in Machine Learning and AI development
Strong understanding of ML algorithms, statistics, optimization, and evaluation techniques
Proficiency in Python for data processing, modeling, and API development
Practical experience with PyTorch or TensorFlow
Strong expertise in dataset engineering and feature engineering
Proven experience deploying ML models into production environments
Solid understanding of Docker and backend system integration
Strong analytical thinking and problem-solving skills

Nice to have

Experience building NLP systems and text-based ML pipelines
Exposure to MLOps practices, CI/CD workflows, and monitoring tools
Experience with distributed systems and load balancing
Familiarity with vector databases and embedding-based retrieval systems
Basic exposure to LLMs, RAG architectures, or agent-based workflows

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Senior Machine Learning & AI Engineer

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