Generative AI Engineer

Hiring: W2 Candidates Only

Location: USA

Visa: Open to any visa type with valid work authorization in the USA

Job Description:

We are seeking a skilled and innovative Generative AI Engineer to design, develop, and deploy cutting-edge AI systems capable of generating high-quality content, such as text, images, audio, video, or code. The ideal candidate will have a strong background in machine learning, deep learning, and practical experience with state-of-the-art generative models like LLMs (e.g., GPT), diffusion models, or GANs.

Key Responsibilities:

• Design, develop, and optimize generative AI models to meet specific product or research goals.
• Fine-tune pre-trained models on domain-specific data to improve performance and relevance.
• Build pipelines for data collection, preprocessing, training, and evaluation.
• Integrate generative AI models into applications, APIs, or production systems.
• Collaborate with product managers, data scientists, and engineers to define use cases and deliver solutions.
• Monitor, evaluate, and improve model performance, scalability, and ethical considerations.
• Stay up to date with the latest research, tools, and best practices in the generative AI space.
• Document methodologies, experiments, and deliver clear technical reports.

Required Skills and Qualifications:

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field.
• 5+ years of hands-on experience with machine learning and deep learning frameworks (TensorFlow, PyTorch).
• Proven experience working with generative models such as LLMs, GANs, VAEs, or diffusion models.
• Strong programming skills in Python; experience with APIs and cloud services is a plus.
• Knowledge of prompt engineering, fine-tuning, and responsible AI practices.
• Solid understanding of data pipelines, MLOps, and model deployment.
• Excellent problem-solving skills, curiosity, and ability to work independently and collaboratively.

Preferred Qualifications:

• Experience working with transformer architectures and large-scale model training.
• Contributions to open-source AI projects or published research papers in generative AI.
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
• Experience deploying AI models to production in cloud environments (AWS, Google Cloud Platform, Azure).