From $85/yr

Customer Engineer

United Statesmid

OtherCustomer EngineerData & AICustomer Data Engineer

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Quick Summary

Key Responsibilities

Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues. Guide customers in optimizing GPU performance for ML training and inference workloads,

Requirements Summary

Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.

Technical Tools

OtherCustomer EngineerData & AICustomer Data Engineer

Responsibilities

~1 min read

→Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
→Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
→Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
→Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
→Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
Experience with Kubernetes and Python programming.
Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
Customer-centric approach with a proven ability to build trust and foster long-term relationships.
Strong ability to explain technical concepts to technical and non-technical audiences.

Nice to Have

~1 min read

Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
Proven experience mentoring technical teams and driving team growth.
Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.