Description

Robusta assists organizations in transitioning to a digital-first approach, crafting unforgettable experiences for their customers. We provide strategy, design, product, and technology services to prominent businesses and brands, utilizing our go-to-market expertise to facilitate seamless customer experiences and enhance conversion rates.

We’re looking for a Senior MLOps Engineer to lead the design, deployment, and scaling of machine learning systems in production. You’ll work at the intersection of data science, software engineering, and infrastructure to ensure reliable, efficient, and scalable ML pipelines. This role is ideal for someone who thrives in building robust systems and enabling teams to move faster with high-quality ML workflows.

Responsibilities

• Design, build, and maintain scalable ML pipelines for training, testing, and deployment
• Deploy & maintain machine learning models and ensure their performance, reliability, and monitoring
• Collaborate with data scientists and engineers to streamline experimentation and deployment workflows
• Implement CI/CD practices for ML systems (ML CI/CD)
• Manage and optimize cloud-based infrastructure for ML workloads
• Develop monitoring, logging, and alerting systems for model performance and data drift
• Ensure reproducibility, versioning, and governance of ML models and datasets
• Advocate for best practices in MLOps, DevOps, and software engineering

Requirements

• 5+ years of experience in software engineering, DevOps, or MLOps roles
• Strong programming skills in Python (and familiarity with Java/Go is a plus)
• Experience with ML frameworks such as TensorFlow, PyTorch, or similar
• Hands-on experience with containerization and orchestration tools (Docker, Kubernetes)
• Experience with cloud platforms (AWS, GCP, or Azure)
• Familiarity with CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI)
• Strong understanding of data pipelines, distributed systems, and API development
• Experience with monitoring tools and logging frameworks