Machine Learning Engineer â Generative AI & MLOps
Machine Learning Engineer â Generative AI & MLOps
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1 Vacancy
Job Description
About CloudBees
CloudBees is the leading software delivery platform for modern enterprises helping organizations accelerate innovation by streamlining and scaling DevOps. As a startup rooted in the developer operations space were building the next generation of intelligent software delivery toolspowered by AI built for scale.
As a member of the AI Foundations founding team this is a high-impact role that sits at the intersection of artificial intelligence and software delivery ideal for someone passionate about pushing the boundaries of developer productivity and intelligent automation.
The Role
CloudBees is seeking a Machine Learning Engineer with hands-on experience in generative AI platforms like Amazon Bedrock and Google Vertex AI as well as expertise in building and maintaining scalable ML this role you will design implement and optimize ML workflows and models that support intelligent automation and insights across the CloudBees product suite.
Youll be part of a fast-paced collaborative and forward-thinking team with the opportunity to make a direct impact on product direction and user experience. With the rapidly changing AI ecosystem being able to apply the right tool at the right time and identify areas the team needs to invest in is critical.
Key Responsibilities
- Design build and maintain production-ready ML pipelines from data ingestion to model deployment and monitoring.
- Integrate and fine-tune foundation models and generative AI services using Amazon Bedrock Google Vertex AI or similar platforms.
- Collaborate with software engineers product managers and data scientists to deliver intelligent features embedded in DevOps tools.
- Automate model retraining versioning testing and CI/CD processes across environments.
- Implement observability and reliability into ML systems ensuring scalability and performance.
- Contribute to the technical roadmap for AI/ML development within the CloudBees platform.
- Document systems and share best practices across teams.
Required Qualifications
- 4 years of experience in machine learning engineering or applied ML roles.
- Hands-on experience with Amazon Bedrock and/or Google Vertex AI for deploying and customizing foundation models.
- Strong understanding of ML lifecycle management and workflow orchestration (e.g. Airflow Kubeflow MLflow).
- Experience with Python TensorFlow PyTorch or similar ML frameworks.
- Proficiency in cloud platforms (AWS and/or GCP) and containerized environments (e.g. Docker Kubernetes).
- Familiar with the modern LLM training stack (eg. the Hugging Face ecosystem PEFT etc.)
- Experience in a startup or fast-paced product development environment.
- Familiarity with version control CI/CD and infrastructure as code (e.g. Terraform GitHub Actions).
- Experience with evaluations
- LLM - large language model
Preferred Qualifications
- Background in generative AI applications (e.g. LLMs embeddings RAG architecture).
- Experience integrating ML systems into SaaS or DevOps platforms.
- Knowledge of data governance privacy and security in machine learning applications.
Why Join CloudBees
- Be part of an innovative AI-driven future in the DevOps ecosystem.
- Work in a dynamic remote-first startup environment with global reach.
- Influence technical strategy and contribute to high-impact product capabilities.
- Competitive compensation equity options and benefits.
CloudBees is an Equal Opportunity Employer. We celebrate diversity and are committed to building an inclusive team.
Employment Type
Full-Time
