AI Platform Engineer

BrothersTech; United States; Presencial; USD 140.000 - 200.000; Jornada completa

Descripción de la vacante

BrothersTech seeks an experienced AI Infrastructure Engineer to design scalable platforms for AI/ML workloads and to build infrastructure for training, deployment, and serving of models. You will implement model-serving infrastructure for LLMs and traditional ML models, and collaborate with data scientists, ML engineers, software engineers, and DevOps teams.

The role requires hands-on experience with Docker, Kubernetes, and cloud-native technologies, plus strong Python, problem-solving, and

Formación

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• Equivalent practical experience may be considered.

Responsabilidades

• Design and develop scalable platforms for AI and machine learning workloads.
• Build and maintain infrastructure for training, deploying, and serving AI models.
• Develop automated CI/CD pipelines for AI applications and machine learning models.
• Deploy and manage AI services using Docker, Kubernetes, and cloud-native technologies.
• Implement model-serving infrastructure for LLMs, generative AI, and traditional ML models.
• Collaborate with data scientists, ML engineers, software engineers, and DevOps teams.
• Troubleshoot platform issues and ensure high availability, scalability, and reliability.

Conocimientos

Python programming

Problem solving

Independent work

Communication

Educación

Bachelor's or Master's in CS/AI/Software Eng

Herramientas

Docker

Kubernetes

Terraform

Jenkins

GitHub Actions

GitLab CI/CD

Prometheus

Grafana

Descripción del empleo

• Design and develop scalable platforms for AI and machine learning workloads.
• Build and maintain infrastructure for training, deploying, and serving AI models.
• Develop automated CI/CD pipelines for AI applications and machine learning models.
• Deploy and manage AI services using Docker, Kubernetes, and cloud-native technologies.
• Implement model-serving infrastructure for LLMs, generative AI, and traditional ML models.
• Integrate foundation models, embedding models, vector databases, and AI APIs into enterprise platforms.
• Build reusable APIs, SDKs, and platform components for AI development teams.
• Implement monitoring, logging, observability, and performance optimization for AI workloads.
• Manage GPU resources, distributed computing, and inference workloads.
• Implement access controls, secrets management, and security policies for AI platforms.
• Collaborate with data scientists, ML engineers, software engineers, and DevOps teams.
• Troubleshoot platform issues and ensure high availability, scalability, and reliability.

Required Technical Skills

• Strong programming experience in Python.
• Experience with AWS, Microsoft Azure, or Google Cloud Platform.
• Hands-on experience with Docker and Kubernetes.
• Knowledge of CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI/CD.
• Understanding of MLOps principles and ML model deployment.
• Experience with REST APIs, microservices, and distributed systems.
• Familiarity with model-serving frameworks such as vLLM, NVIDIA Triton Inference Server, or TorchServe.
• Knowledge of infrastructure as code using Terraform or similar tools.
• Experience with monitoring tools such as Prometheus and Grafana.
• Understanding of authentication, authorization, API security, and secrets management.

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• Equivalent practical experience may be considered.

Candidate Requirements

• 3–5 years of experience in AI infrastructure, platform engineering, MLOps, or cloud engineering.
• Hands-on experience deploying production AI or ML services.
• Strong troubleshooting and problem-solving skills.
• Ability to work independently and collaborate across engineering teams.
• Excellent communication and documentation skills.