Overview
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. You will not only design and build the operational backbone for our clients' AI systems but also guide a talented team of engineers to do the same. 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.
Responsibilities
Lead the Technical Delivery Team
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- 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
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- Architect, design, and implement robust and automated CI/CD pipelines specifically for AI/ML models and applications. Your work will enable the rapid and reliable deployment of cutting-edge agentic AI solutions.
Oversee Production AI Systems
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- Take charge of the operational strategy for our clients' AI environments. This includes overseeing the monitoring, scaling, maintenance, and security of production AI systems to ensure they meet stringent enterprise-grade requirements.
Manage Project Delivery and Issues
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- Concurrently manage the technical execution of multiple customer-facing project delivery activities. You will be the primary technical point of contact for navigating and resolving issues that could impact project timeline, cost, scope, or effectiveness, driving them to a successful resolution.
Drive Stakeholder Communication
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- Lead the presentation of project delivery status, performance metrics, and technical issue resolution plans to both internal Penguin Solutions audiences and to customers. You will be responsible for driving clear, transparent communication regarding all technical aspects of the project.
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
Preferred Qualifications
- 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 pay ultimately offered may vary based on business considerations, including job-related knowledge, skills, experience, and education. The position is bonus-eligible, and there are medical, dental, and vision benefits available. There is a 401k saving plan and 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.