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Senior Machine Learning & AI Engineer

Cogniter Technologies

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Location:
India , Chandigarh

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Contract Type:
Not provided

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Salary:

Not provided

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

Additional Information:

Job Posted:
February 19, 2026

Employment Type:
Fulltime
Work Type:
On-site work
Job Link Share:

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