AI/ML Architect
4 weeks ago
We are seeking a seasoned AI/ML Architect to enhance our talented team. The role demands an individual with significant expertise in both traditional Machine Learning & newer Artificial Intelligence engineering and infrastructure, with an emphasis on Generative AI based systems. A thorough knowledge of public cloud platforms, specifically AWS, is crucial. This remote position calls for exceptional communication skills and a knack for independently tackling complex challenges with innovative solutions.
Key Responsibilities:
- Develop and implement automation and DevOps methodologies, including CI/CD, Infrastructure as Code (IaC), and containerization, to establish a scalable Machine Learning and Artificial Intelligence infrastructure.
- Design and execute automation strategies, encompassing DevOps pipelines, scripting, and Terraform-based Infrastructure as Code.
- Engage actively in client sessions to understand and address their needs.
- Prepare and maintain detailed technical documentation.
Requirements:
- Experienced with machine learning frameworks (TensorFlow, PyTorch) and libraries (scikit-learn).
- Proven hands-on experience with generative AI architectures, including design, training, and customization for LLM in text-to-text, image-to-text, and/or text-to-image projects.
- Implement and customize generative AI architectures and approaches such as finetuning transformer based LLMs using PEFT methods like LoRA, QLoRA, etc.
- Expertise in public cloud services, particularly in AWS.
- Experienced working with Sagemaker, Bedrock, and other AWS AI and Machine learning services.
- Experience with AWS managed services and understanding of cloud-based messaging/stream processing systems are critical.
Must Have:
- AWS Cloud Professional level certification in AI/ML, Architecture, and Data.
- 10+ years of experience in customer-facing software/technology or consulting.
- 5+ years of experience with "on-premises to cloud" migrations or IT transformations.
- 5+ years of experience building, and operating solutions built on AWS (ideally) or Azure/GCP.
- Technical degree: Computer Science, software engineering, or related.
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