We are posting this job on behalf of our client.

Full-Time

Having experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-based AI deployments. Someone who can lead the team.

Responsibilities:

- Design, develop, and deploy Machine Learning and Deep Learning models for classification,

regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.
- Build and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, evaluation, and deployment.
- Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related frameworks.
- Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama,

Claude, and Stable Diffusion.
- Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.
- Optimize model performance, scalability, and reliability for production environments.
- Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.




- Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence,

Mathematics, or a related field.
- 7+ years of hands-on experience in AI/ML product development.
- Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and

Hugging Face.
- Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.
- Robust understanding of the ML lifecycle including model training, tuning, deployment,

monitoring, and optimization.
- Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.
- Experience with AWS, Azure, or GCP cloud platforms.
- Strong problem-solving and analytical skills.Preferred Skills
- Fine-tuning and deployment of Large Language Models.
- Experience with RAG (Retrieval Augmented Generation) architectures.
- Contributions to open-source AI projects or research publications.
- Knowledge of model interpretability, data annotation, and feature engineering.
- C++ experience for high-performance AI applications.

📌 Data science (Ahmedabad)
🏢 Filuet
📍 Ahmedabad