Job Details

Skills

• Job Title: Senior Machine Learning & AI Engineer

   

  Location: Chandigarh, India (On-site)
  Experience: 3–5+ Years
  Employment Type: Full-Time

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  About the Role

   

  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.

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  Key Responsibilities

  Machine Learning & AI Development

   

  • 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

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  Dataset Engineering & Data Pipelines

   

  • 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

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  Deep Learning & NLP

   

  • 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

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  Backend APIs & Model Serving

   

  • 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

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  Model Deployment & Infrastructure

   

  • 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

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  Generative AI & Agentic Frameworks (Secondary Focus)

   

  • 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

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  Collaboration & Technical Leadership

   

  • 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

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  Required Skills & Qualifications

   

  • 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

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  Preferred Qualifications

   

  • 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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  How to Apply

   

  Email your updated resume to hr@cogniter.com
  Subject: Application for Senior Machine Learning & AI Engineer – [Your Name]

  Only shortlisted candidates will be contacted.