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AI/ML Engineer with LLM and Advanced AI Methods Experience

2 weeks ago

Bengaluru, Karnataka, India Enterprise AI-ML Automation Inc. Full time

Overview

We are looking for a highly skilled AI/ML Engineer with expertise in retrieval-augmented generation (RAG), model fine-tuning and AI Agents. The ideal candidate is a person who thrives on independent problem-solving — someone who can take a loosely defined challenge, explore solution paths, make informed decisions, and clearly present their approach. The ideal candidate will be comfortable owning ideas from inception through implementation in scalable, production-grade systems.

Responsibilities:

  • AI Model Development and Fine-Tuning:
  • Fine-tune large language models (LLMs) including generating training data, running experiments and optimizing hyperparameters.
  • Implement and optimize retrieval-augmented generation (RAG) techniques.
  • Experiment with different model architectures and fine-tuning strategies.
    • AI Agents and Advanced AI Methods:
    • Implement AI agents, multi-agent systems and other advanced AI techniques to meet business needs.
    • Develop innovative solutions using cutting-edge AI technologies and methodologies.
    • Stay updated with the latest research and advancements in AI/ML.
      • Data Management and Preprocessing:
      • Implement production grade systems to collect, preprocess, and manage large datasets for training and evaluation.
      • Implement data augmentation and feature engineering techniques to improve model performance.
      • Ensure data quality and integrity throughout the AI/ML pipeline.
        • Model Evaluation and Optimization:
        • Evaluate model performance using appropriate metrics and benchmarks.
        • Optimize models for speed, efficiency, and scalability.
        • Conduct thorough testing and validation of AI models.
          • Integration and Deployment:
          • Collaborate with software engineers to integrate AI models into production systems.
          • Develop APIs and interfaces for seamless interaction with AI models.
          • Monitor and maintain deployed models, ensuring their continued performance and accuracy.
            • Collaboration and Communication:
            • Work closely with cross-functional teams to understand requirements and deliver AI solutions.
            • Communicate complex technical concepts to non-technical stakeholders.
            • Provide technical guidance and mentorship to junior team members.

Qualifications

  • Education and Experience:
  • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • 3+ years of experience in AI/ML engineering with a focus on building AI agentic systems and model fine-tuning.
    • Technical Skills:
    • Strong proficiency in Python and ML frameworks (PyTorch, etc.).
    • Knowledge of software engineering best practices and version control systems (Git).
    • Experience with large language models (GPT, BERT, Llama, etc.) and retrieval-augmented generation (RAG).
    • Proficient in fine-tuning pre-trained models for specific tasks.
    • Solid understanding of advanced AI methods, including AI agents and multi-agent systems.
    • Experience with data preprocessing, augmentation, and feature engineering.
    • Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
      • Soft Skills:
      • Excellent problem-solving and analytical skills.
      • Strong builder mentality and comfortable writing production grade code using Git.
      • Strong communication and teamwork abilities.
      • Ability to work in a fast-paced, startup environment.
      • Attention to detail and a commitment to delivering high-quality work.
        • Preferred Qualifications:
        • Contributions and/or publications within the AI/ML research community and experience bringing AI/ML ideas to reality
        • Experience or knowledge of networking and security (campus, datacenter or cloud).
        • Experience using AI Dev Tools, including for coding, for substantial improvements to productivity