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Senior AI ML Engineer

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Onsite

Senior AI ML Engineer

Impelsys

Senior AI ML Engineer

Skills

MongoDBDeep LearningDockerPythonMicroservicesNumPypandasPyTorchTensorFlowMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingAzure

7 days ago

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Important information


Location:

Karnataka, India

Work mode:

Onsite

Published on:

15 October 2026

What they need


Work Location: Bangalore

Experience: 5+ years

Job Overview

As a Senior AI ML Engineer, you will be responsible for designing, developing, and deploying scalable machine learning models and AI systems in production environments. You will work closely with junior ML engineer and other product stakeholders to build advanced AI solutions, with a strong focus on Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise-grade ML systems.

Key Responsibilities

  • Design, develop, and deploy machine learning models and advanced AI systems, including LLMs and RAG architectures
  • Build and maintain scalable ML pipelines for data ingestion, preprocessing, model training, validation, and deployment
  • Optimize and fine-tune models for performance, scalability, and cost efficiency
  • Develop and integrate embedding models and vector database solutions
  • Implement and maintain MLOps pipelines, CI/CD workflows, and model monitoring systems
  • Integrate ML models into production applications using APIs and microservices architecture
  • Lead experimentation, model evaluation, and A/B testing initiatives
  • Work closely with cross-functional teams to translate business problems into AI-driven solutions
  • Ensure robustness, reliability, and security of ML systems in production
  • Mentor junior engineers and contribute to AI/ML best practices within the organization

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
  • 5+ years of experience in Machine Learning engineering or AI development
  • Strong programming expertise in Python
  • Extensive experience with:
    • Data manipulation and analysis libraries: pandas, numpy
    • Machine learning frameworks: scikit-learn, TensorFlow, PyTorch
    • NLP libraries: Hugging Face Transformers, spaCy, NLTK
  • Strong proficiency in working with large datasets
  • Experience with cloud platforms (AWS, Azure) and ML services
  • Solid understanding of machine learning algorithms, deep learning, and statistical modeling
  • Hands-on experience with Docker, Kubernetes, and CI/CD pipelines
  • Experience working with REST APIs and microservices architecture

Preferred Qualifications

  • Experience with Large Language Models (LLMs), prompt engineering, and fine-tuning
  • Hands-on experience with Retrieval-Augmented Generation (RAG) systems
  • Experience with vector databases (e.g., Pinecone, Azure Index)
  • Practical experience implementing MLOps best practices
  • Experience with distributed computing frameworks (e.g., Spark)
  • Familiarity with NoSQL databases (e.g., MongoDB)
  • Experience leading AI initiatives or mentoring junior engineers
  • Contributions to AI research, publications, or open-source projects

Skills and Attributes

  • Strong analytical and problem-solving abilities
  • Excellent communication and stakeholder management skills
  • Ability to lead technical discussions and mentor team members
  • Strong ownership mindset and accountability
  • Passion for staying updated with advancements in AI, NLP, and Generative AI
  • Ability to explain complex AI concepts to non-technical stakeholders

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