[Hiring] Senior AI Engineer @FullStack Labs

Role Description

What We Are Looking For:

• 5+ years of professional experience in AI/ML engineering, software engineering, or machine learning infrastructure.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Strong hands-on experience with NVIDIA's AI inference stack, particularly NVIDIA NIM, NeMo, NeMo Guardrails, TensorRT-LLM, and Triton Inference Server.
• Proven experience deploying and self-hosting LLMs and embedding models in production on GPU infrastructure.
• Practical experience serving and scaling inference workloads, including GPU cluster operations and Kubernetes-based environments, ideally using the NVIDIA GPU Operator.
• Strong theoretical and applied understanding of LLMs, including inference optimization, model serving, and the operational challenges of running models at scale.
• Experience building and operating private, on-premises AI inference platforms in secure environments.
• Ability to implement guardrails and controls for production LLM applications.
• Experience working in banking or other regulated industries is a plus.
• Ability to work through new and difficult issues and contribute to libraries as needed.
• Ability to create and maintain continuous integration and delivery of applications.
• Forensic attention to detail.
• A positive mindset and a can-do attitude.
• Experience working on Agile / Scrum teams.
• Meaningful experience working on large, complex systems.
• Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
• Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.

Qualifications

• 5+ years of professional experience in AI/ML engineering, software engineering, or machine learning infrastructure.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Strong hands-on experience with NVIDIA's AI inference stack, particularly NVIDIA NIM, NeMo, NeMo Guardrails, TensorRT-LLM, and Triton Inference Server.
• Proven experience deploying and self-hosting LLMs and embedding models in production on GPU infrastructure.
• Practical experience serving and scaling inference workloads, including GPU cluster operations and Kubernetes-based environments, ideally using the NVIDIA GPU Operator.
• Strong theoretical and applied understanding of LLMs, including inference optimization, model serving, and the operational challenges of running models at scale.
• Experience building and operating private, on-premises AI inference platforms in secure environments.
• Ability to implement guardrails and controls for production LLM applications.
• Experience working in banking or other regulated industries is a plus.
• Ability to work through new and difficult issues and contribute to libraries as needed.
• Ability to create and maintain continuous integration and delivery of applications.
• Forensic attention to detail.
• A positive mindset and a can-do attitude.
• Experience working on Agile / Scrum teams.
• Meaningful experience working on large, complex systems.
• Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
• Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.

Requirements

• 5+ years of professional experience in AI/ML engineering, software engineering, or machine learning infrastructure.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Strong hands-on experience with NVIDIA's AI inference stack, particularly NVIDIA NIM, NeMo, NeMo Guardrails, TensorRT-LLM, and Triton Inference Server.
• Proven experience deploying and self-hosting LLMs and embedding models in production on GPU infrastructure.
• Practical experience serving and scaling inference workloads, including GPU cluster operations and Kubernetes-based environments, ideally using the NVIDIA GPU Operator.
• Strong theoretical and applied understanding of LLMs, including inference optimization, model serving, and the operational challenges of running models at scale.
• Experience building and operating private, on-premises AI inference platforms in secure environments.
• Ability to implement guardrails and controls for production LLM applications.
• Experience working in banking or other regulated industries is a plus.
• Ability to work through new and difficult issues and contribute to libraries as needed.
• Ability to create and maintain continuous integration and delivery of applications.
• Forensic attention to detail.
• A positive mindset and a can-do attitude.
• Experience working on Agile / Scrum teams.
• Meaningful experience working on large, complex systems.
• Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
• Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.

Benefits

• Competitive pay.
• 100% remote work.
• The ability to work with leading startups and Fortune 500 companies.
• Continuing education opportunities.
• Opportunity to grow and expand your career.

Company Description

Our talent network is committed to fostering a diverse, inclusive, and accessible environment where IT professionals can find opportunities that match their skills. We welcome individuals of all races, religions, genders, sexual orientations, national origins, abilities, and experiences. Our focus is on connecting talent with projects based on qualifications, ensuring a fair and transparent process that values diverse perspectives and global collaboration.