AI/ML Innovator

3 days ago

Delhi, Delhi, India beBeeArtificial Full time US$ 1,20,000 - US$ 1,70,000
Job Overview

As a seasoned AI/ML Engineer, you will be at the forefront of designing, developing, and deploying innovative AI and ML solutions that drive business value.

Key responsibilities include crafting cutting-edge machine learning models, including Generative AI, Large Language Models, and Deep learning architectures.

Your role involves optimizing, fine-tuning, and scaling these models while ensuring they meet performance objectives and integrate effectively with existing systems.

You will collaborate closely with cross-functional teams to develop production-ready AI solutions that meet business needs.

Responsibilities:

  • Develop, optimize, and deploy machine learning and deep learning models, including LLMs and Generative AI models.
  • Design scalable, AI-powered solutions that integrate into existing systems.
  • Fine-tune and evaluate models on large-scale datasets to improve accuracy, efficiency, and robustness.
  • Collaborate with software engineers, data scientists, and product teams to align AI models with business objectives.
  • Work with healthcare and claims data to build high-performance AI systems.
  • Develop and maintain MLOps pipelines for training, deploying, and monitoring AI models.
  • Troubleshoot and resolve AI/ML engineering challenges, ensuring models perform effectively in production.
  • Stay up-to-date with advancements in AI and ML to continuously improve solutions.
  • Document AI/ML workflows, methodologies, and best practices for internal knowledge sharing.

Requirements:

  • Bachelor's or Master's degree in a quantitative field such as Computer Science or Data Science or related disciplines.
  • Minimum 3+ years' experience in data science/ML role, with a track record of delivering impactful solutions in a production environment.
  • Proficiency in programming languages like Python, R, and SQL, with experience in building scalable and efficient ML/NLP workflows.
  • Deep understanding and hands-on experience in Machine Learning, Deep Learning, and Natural Language Processing.
  • Experience in working with state-of-the-art Generative AI models, including model finetuning and evaluation techniques.
  • Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data.
  • Cloud computing and deployment knowledge for deploying and managing AI applications on cloud platforms.

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