onsite
Applied AI Engineer - Jobgether
AI Engineer
Design and implement scalable AI infrastructure that enables teams to develop, deploy, and operate LLM and machine‑learning products, leveraging cloud services, container orchestration, and modern MLOps practices.
About the role
Key Responsibilities
- Architect and build platform components that support the end‑to‑end lifecycle of large language models and other ML workloads.
- Develop reusable libraries, APIs, and tooling to accelerate AI product development across multiple teams.
- Implement CI/CD pipelines, monitoring, and automated scaling for model training and inference in cloud environments.
- Collaborate with data scientists, product engineers, and security teams to ensure robust, secure, and cost‑effective AI solutions.
- Evaluate emerging AI technologies and integrate best‑in‑class frameworks and services into the platform.
Requirements
- Strong programming skills in Python and experience with deep‑learning frameworks such as TensorFlow or PyTorch.
- Hands‑on experience designing, deploying, and managing ML workloads on cloud platforms (e.g., AWS) using containers and orchestration tools like Docker and Kubernetes.
- Proven knowledge of MLOps practices, including model versioning, automated testing, and monitoring.
- Familiarity with large language models (LLMs) and techniques for fine‑tuning, serving, and scaling them.
- Excellent problem‑solving abilities and a collaborative mindset for working across multidisciplinary teams.
Skills
pythontensorflowpytorchawskubernetesmlops