Gen AI Specialist

1 week ago

Chennai, Tamil Nadu, India Ford Motor Full time ₹ 12,00,000 - ₹ 36,00,000 per year
Description
We are seeking a highly motivated and skilled AI Engineer with 3+ years of experience specializing in Generative AI and Agentic Systems. The ideal candidate will be instrumental in designing, developing, and deploying advanced AI models and autonomous agents that can understand, generate, and interact with complex environments. You will work on exciting projects that push the boundaries of AI, from creating sophisticated content generation tools to developing intelligent agents capable of complex decision-making and problem-solving.

Responsibilities
  • Model Development & Implementation: Design, develop, and implement state-of-the-art generative AI models (e.g., Large Language Models (LLMs), Diffusion Models, GANs, VAEs, Transformers) for various applications such as text generation, image synthesis, code generation, and data augmentation.
  • Agentic System Design: Architect and build autonomous AI agents capable of planning, reasoning, learning from interaction, and executing complex tasks in dynamic environments. This includes developing multi-agent systems and integrating them with existing platforms.
  • Data Engineering: Prepare, preprocess, and manage large datasets for training and evaluating generative and agentic AI models, ensuring data quality and relevance.
  • Research & Innovation: Stay abreast of the latest research and developments in Generative AI, Agentic AI, and Machine Learning. Experiment with new algorithms, frameworks, and techniques to continuously improve model performance and capabilities.
  • Evaluation & Optimization: Develop robust evaluation metrics and conduct rigorous testing to assess model performance, reliability, and ethical implications. Optimize models for efficiency, scalability, and deployment in production environments.
  • System Integration: Integrate developed AI models and agentic systems into existing software architectures and applications, collaborating closely with MLOps, backend, and frontend teams.
  • Collaboration & Communication: Work effectively within cross-functional teams, communicate technical concepts clearly, and contribute to a collaborative and innovative team culture.
  • Problem Solving: Identify and troubleshoot complex technical issues related to AI model development, deployment, and performance


Qualifications
  • Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a closely related quantitative field.
  • Experience: 3+ years of hands-on experience in AI/ML development, with a significant focus on Generative AI and/or Agentic Systems.
  • Programming Skills: Strong proficiency in Python and experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers, Keras, Scikit-learn).
  • Generative Models: Proven experience with various generative models (LLMs, GANs, VAEs, Diffusion Models, Transformers) and understanding of their underlying principles.
  • Agentic AI Concepts: Familiarity with agent architectures, reinforcement learning fundamentals, planning algorithms, multi-agent systems, and prompt engineering for LLM-based agents.
  • Mathematical Foundation: Solid understanding of linear algebra, calculus, probability, and statistics as applied to machine learning.
  • Problem-Solving: Excellent analytical and problem-solving skills, with the ability to tackle complex technical challenges creatively.
  • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices for deploying and managing AI models at scale.
  • Familiarity with agentic AI frameworks such as LangChain, LlamaIndex, AutoGPT, or similar.
  • Experience with distributed computing frameworks (e.g., Spark, Dask).
  • Knowledge of natural language processing (NLP) or computer vision techniques.
  • Contributions to open-source projects or relevant publications in AI conferences/journals.
  • Strong communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.
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