AI/MLOps Engineer

Our client is a Silicon Valley company specialising in Vertical AI SaaS solutions, collaborating with top firms worldwide in industries such as accounting, consulting, investment banking, legal, private capital, and real assets.

They’re looking for a driven DevOps Engineer to join the Cloud Engineering team and revolutionise how AI models are developed and deployed. You'll bridge the gap between data science and operations, helping turn innovative projects in machine learning, traditional AI, and Generative AI from concept into reality.

Key Responsibilities:

• Cross-Team Collaboration: Work with multiple product teams to implement security, data protection, and MLOps strategies that drive business growth and ensure high availability for AI/ML workloads.
• Continuous Deployment: Implement and manage CD pipelines using tools such as ArgoCD and Helm.
• Cloud Infrastructure: Design, deploy, and maintain scalable, enterprise-grade cloud environments for ML workloads using Kubernetes, while ensuring compliance with security standards.
• Infrastructure as Code: Develop and manage infrastructure using Terraform to enable consistency and automation.
• Monitoring and Logging: Implement model performance, cost, and drift monitoring, along with logging practices using tools like Prometheus and Langfuse.
• ML Pipeline Automation: Build and automate end-to-end ML pipelines covering data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• MLOps Enablement: Promote MLOps best practices across the organsation through mentorship and training on tools and methodologies.

What You Bring:

• Education: Bachelor’s degree in Computer Science or a related field.
• Technical Experience: 5+ years of experience in technical roles, ideally within a SaaS environment.
• Infrastructure & DevOps: At least 4 years of experience in Infrastructure, DevOps, or MLOps.
• Cloud & CI/CD Expertise: Experience in cloud platforms (e.g., Microsoft Azure), containerisation technologies (e.g., Docker, Kubernetes), and CI/CD tools (e.g., ArgoCD, Azure DevOps, Helm).
• Cloud Architecture: Ability to design scalable, secure, and efficient cloud systems with familiarity in enterprise-grade security and compliance standards.
• Continuous Learning: Demonstrated curiosity and drive to explore emerging trends in Generative AI and Agentic AI.
• Collaboration & Culture: Passion for teamwork, problem-solving, and fostering a culture of continuous improvement.

Valued Experience:

• Machine Learning Experience: Preferred experience deploying or managing ML systems in production, with a solid understanding of ML concepts and interest in AI/ML.
• MLOps Practices: Familiarity with LLM/MLOps best practices is an advantage.
• Programming Skills: Proficient in Python programming.

Why Apply Now?

With over 20 years of expertise, our client is a global leader in Vertical AI SaaS solutions, revolutionising how top firms across industries operate. They offer more than just a job—it’s a chance to be part of a company that values accountability, collaboration, and growth in a truly diverse and inclusive culture. They provide a flexible, connected work environment that prioritises both work-life balance and career development, making it the perfect place to thrive professionally and personally.

Are you ready to take the next step in your career? Send your CV to ari.kilab@robertwalters.com