Job Description

Skills

Job Title: Senior Machine Learning & AI Engineer

Location: Chandigarh, India (On-site)
Experience: 3.5+ Years
Employment Type: Full-Time


About the Role

Cogniter Technologies is hiring a Senior Machine Learning & AI Engineer to design, develop, and deploy scalable, production-ready machine learning and AI solutions. This role primarily focuses on classical machine learning, deep learning, dataset engineering, and enterprise-grade deployment.


Generative AI and agentic frameworks will be applied selectively and only where they deliver clear and measurable business value.


The ideal candidate has strong foundations in machine learning, hands-on experience across the full AI lifecycle, and the ability to take models from data collection to reliable production deployment.

Key Responsibilities


Machine Learning & AI Development

  • Design, develop, and train 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 model performance using metrics such as precision, recall, F1-score, and ROC-AUC

  • Perform hyperparameter tuning to improve model accuracy, robustness, and generalization


    • Dataset Engineering & Data Pipelines

  • Create, clean, augment, and manage large-scale datasets

  • Design synthetic and semi-synthetic data pipelines when labeled data is limited

  • Ensure data quality, consistency, and dataset version control

  • Collaborate with data teams to build efficient ETL and feature pipelines


    • Deep Learning & NLP

  • Develop and fine-tune deep learning models using PyTorch or TensorFlow

  • Build NLP pipelines for classification, semantic search, information extraction, and information retrieval

  • Optimize neural networks using regularization, pruning, quantization, and transfer learning


    • Backend APIs & Model Serving

  • Build Python-based APIs using FastAPI or Flask

  • Implement batch and real-time inference pipelines

  • Optimize inference services for low latency, high throughput, and fault tolerance

  • Integrate AI services into existing enterprise systems


    • Model Deployment & Infrastructure

  • Containerize ML applications using Docker

  • Deploy models in production environments with appropriate resource allocation

  • Implement scalable inference services using load-balancing strategies

  • Monitor model performance, data drift, and inference latency

  • Manage model versioning, rollback, and lifecycle processes


    • Generative AI & Agentic Tools (Secondary Focus)

  • Apply LLMs and Generative AI only where they add tangible business value

  • Implement Retrieval-Augmented Generation (RAG) pipelines when required

  • Use agentic frameworks such as LangChain or LangGraph selectively

  • Ensure factual accuracy, reliability, and controlled outputs


    • Collaboration & Research

  • Work closely with product, backend, and data teams to translate business requirements into ML solutions

  • Stay updated with advancements in machine learning research and system design

  • Participate in architecture discussions, model reviews, and technical planning

    • Required Skills & Qualifications

  • 3+ years of hands-on experience in Machine Learning and AI development

  • Strong understanding of ML algorithms, statistics, and optimization techniques

  • Proficiency in Python for data processing, modeling, and API development

  • Experience with PyTorch or TensorFlow

  • Strong experience in dataset creation, preprocessing, and feature engineering

  • Experience deploying ML models in production environments

  • Solid understanding of Docker and backend system integration

  • Strong analytical and problem-solving skills


    • Preferred Qualifications

  • Experience with NLP systems and text-based ML pipelines

  • Exposure to MLOps, CI/CD pipelines, and monitoring tools

  • Experience with distributed systems and load balancers

  • Familiarity with vector databases and embeddings

  • Basic exposure to LLMs, RAG pipelines, or agentic workflows

    • How to Apply

    Email:
    Subject: Application for Senior Machine Learning & AI Engineer – [Your Name]


    Only shortlisted candidates will be contacted.

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