Lead ML/AI Engineer

Role Description

As the Lead ML/AI Engineer, you will be the technical heart of our post-sales delivery organization. You will be a hands-on, player-coach responsible for leading the team that brings our AI solutions to life for our customers. This role is perfect for a seasoned MLOps expert with a passion for automation, quality, and leadership, who thrives on solving complex technical challenges and ensuring customer success.

• Lead the Technical Delivery Team: Lead, mentor, and provide technical guidance to a team of ML/AI Engineers and AI Infrastructure Specialists. You will be the ultimate owner of the technical quality, reliability, and performance of all deployed solutions.
• Design and Implement MLOps Pipelines: Architect, design, and implement robust and automated CI/CD pipelines specifically for AI/ML models and applications.
• Oversee Production AI Systems: Take charge of the operational strategy for our clients' AI environments, including monitoring, scaling, maintenance, and security of production AI systems.
• Manage Project Delivery and Issues: Concurrently manage the technical execution of multiple customer-facing project delivery activities and resolve issues impacting project timeline, cost, scope, or effectiveness.
• Drive Stakeholder Communication: Lead the presentation of project delivery status, performance metrics, and technical issue resolution plans to both internal and external audiences.

Qualifications

• 7+ years of experience in software engineering, DevOps, or ML engineering, with at least 2 years in a technical leadership, mentorship, or lead engineer capacity.
• Deep, hands-on experience building and managing CI/CD pipelines (e.g., Jenkins, GitLab CI, Actions) and infrastructure-as-code (e.g., Ansible, Terraform, Puppet).
• Strong, production-level experience with containerization (Docker) and container orchestration (Kubernetes).
• Proficiency with monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK Stack).
• Excellent problem-solving and troubleshooting skills, especially in complex, distributed systems.

Requirements

• Specific experience with MLOps platforms and tools (e.g., Kubeflow, MLflow, Seldon Core).
• Hands-on experience with the NVIDIA AI Enterprise stack, particularly Triton Inference Server, TensorRT-LLM, and NeMo.
• Experience in a customer-facing professional services or consulting role.
• Strong scripting and programming skills, particularly in Python or Go.
• Experience with deploying and managing infrastructure in both public cloud (AWS, Azure, GCP) and on-premises data center environments.

Location

This is a remote position in the United States.

Travel

Flexible (with travel to client sites and Penguin Solutions offices as needed).

Compensation & Benefits

• The base pay range that the Company reasonably expects to pay for this position in the United States is $175,000 - $215,000.
• The position is bonus-eligible.
• Medical, dental, and vision benefits available.
• 401k saving plan.
• Other benefits, such as Paid Time Off, Life Insurance, and an Employee Assistance Plan.

Inclusion & Belonging Statement

We are committed to creating an inclusive environment that embraces differences and fosters belonging for all.

Equal Opportunity Statement

We are an Affirmative Action/Equal Opportunity Employer and strongly committed to all policies which will afford equal opportunity employment to all qualified persons without regard to age, national origin, race, ethnicity, creed, gender, disability, veteran status, or any other characteristic protected by law.