ML Platform Deployment Engineer

About Neural Concept 

We build technology that enables engineers to solve complex design challenges faster and more effectively. Our platform leverages 3D deep learning to transform CAE data into real-world results, helping top companies in automotive, aerospace, and energy streamline their R&D. 

The Role 

We’re looking for a Platform Deployment Engineer to lead and oversee the technical onboarding and integration of our platform in enterprise environments. You’ll play a pivotal role in deploying our software as a SaaS solution on customer cloud infrastructure (AWS, Azure, GCP) or on-premise (HPC, VM). Your work directly contributes to customer satisfaction and long-term platform adoption.

This is a highly customer-facing role. We value engineers who are not only technically capable but also excellent communicators, proactive problem-solvers, and trusted advisors to our customers.

• Lead Deployments: Design and implement robust deployment architectures that align with customer IT environments and business goals.

• Architect Solutions: Assess customer needs and tailor scalable cloud/hybrid/on-premise deployments using Kubernetes, Docker, and cloud-native tooling.

• Customer Engagement: Act as a technical point of contact for customers throughout the deployment process, from architecture to troubleshooting.

• Security & Compliance: Own the process of responding to IT and security questionnaires. Ensure compliance with enterprise security and privacy requirements.

• Collaboration & Feedback: Work closely with internal teams (product, R&D, platform) to continuously improve deployment processes and modularity.

• Documentation & Enablement: Produce high-quality documentation, implementation guides, and internal playbooks.

Who You Are 

• Education: Advanced degree in Computer Science, Engineering, or a related field (or equivalent experience).

• Experience: at least 4 years of hands-on experience deploying enterprise software in cloud and/or HPC environments.

• Mandatory Technical Skills: Strong background in Kubernetes, Docker, and/or Singularity, with production experience.

• Customer-facing Skills: Experience working directly with customers to scope, deploy, and maintain infrastructure.

• Cloud Platforms: Proficient with AWS, Azure, or GCP, including security and networking fundamentals.

• Tools: Familiar with Terraform, OAuth2, SAML, Slurm, PBS, and monitoring tools like Prometheus and Grafana.

• Mindset: A proactive communicator and strategic thinker who thrives in dynamic, interdisciplinary teams.

What We Offer