Generative AI Engineer

14 hours ago

Bengaluru, Karnataka, India Weekday AI Full time US$ 1,25,000 - US$ 1,75,000 per year
Job Description:Requirements:Key Responsibilities
  • Design, develop, and deploy Generative AI models (e.g., GANs, VAEs, diffusion models, LLMs) for diverse applications such as image synthesis, text generation, and content automation.
  • Collaborate with cross-functional teams to integrate computer vision solutions with generative models for tasks such as object detection, segmentation, and image enhancement.
  • Implement and fine-tune models using TensorFlow, PyTorch, and transformers architectures.
  • Build robust data pipelines for model training and inference using PySpark, ETL workflows, and big data tools.
  • Create APIs and backend services using Python and RESTful APIs to support seamless deployment and integration of ML models into production environments.
  • Apply advanced techniques in Natural Language Processing (NLP) to support conversational AI, summarization, question answering, and more.
  • Leverage Docker and Kubernetes for containerization and orchestration of scalable AI systems in cloud or hybrid environments.
  • Ensure model reliability, reproducibility, and maintainability using CI/CD pipelines and version control systems.
  • Optimize model performance and system latency for real-time applications.
  • Conduct experiments, perform A/B testing, and continuously monitor performance metrics to drive model improvements.
Skills & Qualifications
  • Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. A PhD is a plus.
  • 7-10 years of industry experience in Machine Learning, Deep Learning, and AI model development.
  • Proven expertise in Generative AI, Computer Vision, and Deep Learning techniques.
  • Proficient in Python, with strong experience using Pandas, NumPy, and data preprocessing libraries.
  • Hands-on experience with ML frameworks: PyTorch, TensorFlow, Hugging Face Transformers.
  • Experience in building scalable data pipelines using ETL and PySpark.
  • Familiarity with NoSQL databases (e.g., MongoDB, DynamoDB) for storing unstructured data.
  • Experience deploying models in production using Docker, Kubernetes, and cloud-native services.
  • Strong understanding of software engineering practices including CI/CD, testing, and code reviews.
  • Experience working in agile teams and collaborating with product and engineering stakeholders.
Nice to Have
  • Exposure to multimodal models combining text, image, and audio.
  • Experience with prompt engineering and fine-tuning foundation models.
  • Contributions to open-source AI projects or published research papers.

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