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Responsibilities
We are seeking an AI/ML Engineer focused on managing and optimizing operational AI/ML pipelines. This role emphasizes the deployment, management, and scaling of AI solutions, with a particular focus on maintaining high-performance systems. You will work with tools like LangChain, Retrieval-Augmented Generation (RAG), and fine-tuning techniques to ensure our models perform optimally under real-world conditions. Experience in model training is a plus but not required; the primary responsibility is to ensure that our models and pipelines are reliable, efficient, and production-ready.
Key Responsibilities
* Develop, deploy, and maintain high-throughput AI/ML pipelines, focusing on stability and scalability.
* Use tools like LangChain to streamline operational workflows and automate tasks within the AI ecosystem.
* Implement Retrieval-Augmented Generation (RAG) techniques to enhance data retrieval and improve model performance.
* Fine-tune existing models to meet specific requirements and maintain model accuracy in production environments.
* Collaborate with data engineers, software engineers, and other team members to optimize data flow and enhance pipeline performance.
* Monitor and troubleshoot issues in production, ensuring minimal downtime and high availability.
* Document processes, best practices, and operational strategies for AI/ML pipeline management.
Qualifications
* Bachelor’s degree in Computer Science, Data Science, or a related field, or equivalent work experience.
* 2+ years of experience managing and deploying AI/ML models in production.
* Familiarity with MLOps principles and tools for automating and scaling AI workflows.
* Ability to work collaboratively in a fast-paced, dynamic environment.
Nice-to-Have
* Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus.
* Familiarity with model training techniques and frameworks like PyTorch, TensorFlow, etc.
* Exposure to large language models and fine-tuning processes.
This job post is closed.