Activate JobCopilot
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior MLOps Engineer based in Brazil.
This is a high-impact platform engineering role focused on building and scaling the foundational infrastructure that powers machine learning and AI across a global product ecosystem.
You will work at the intersection of DevOps, data engineering, and machine learning, enabling teams to deploy and operate AI models at scale with reliability and speed.
The role involves designing cloud-native platforms that support the full ML lifecycle, from experimentation to production-grade deployment.
You will contribute to building self-service tools and abstractions that empower data scientists and engineers to work autonomously and efficiently.
A strong focus is placed on scalability, automation, and standardizing best practices for ML and LLM workflows across the organization.
You will collaborate closely with infrastructure, data, and product teams to ensure seamless integration of ML systems into broader data and governance frameworks.
This position is ideal for engineers who enjoy solving complex platform challenges and enabling large-scale AI innovation.
Accountabilities:
- Design, evolve, and maintain scalable ML infrastructure, including Kubeflow, Feast, and Spark-on-Kubernetes environments.
- Build internal platforms, tools, and APIs that enable self-service ML development and deployment across distributed teams.
- Define and implement MLOps and LLMOps best practices, supporting the full lifecycle from experimentation to production.
- Collaborate with Data Science and engineering teams to standardize CI/CD, versioning, testing, and observability for ML workflows.
- Develop and optimize cloud-native solutions using AWS, Kubernetes, and infrastructure-as-code tools such as Terraform or Crossplane.
- Ensure seamless integration of ML artifacts into enterprise data catalog, privacy, and governance systems.
- Improve developer experience by creating reusable libraries, abstractions, and scalable orchestration frameworks.
- Partner cross-functionally to translate complex ML use cases into robust, production-ready platform solutions.
Requirements:
- Strong experience in DevOps and MLOps, including CI/CD pipelines, infrastructure as code, and observability systems.
- Hands-on expertise with Kubernetes, Kubeflow, Spark, and AWS cloud environments.
- Strong Python development skills, with experience building reusable libraries, APIs, and platform tooling.
- Proven ability to design and operate large-scale ML or data platforms in production environments.
- Experience working closely with Data Science teams to enable scalable ML workflows and deployment pipelines.
- Solid understanding of distributed systems and cloud-native architecture principles.
- Strong systems thinking mindset with the ability to balance platform standards and team autonomy.
- Excellent collaboration and communication skills in cross-functional engineering environments.
- Nice to have: experience with LLMOps, advanced ML orchestration, or data governance frameworks.
Benefits:
- Fully remote position within Brazil with flexible work arrangements.
- Comprehensive health, dental, and life insurance coverage.
- Flexible benefits program tailored to individual needs.
- Paid time off including vacation, additional annual days, and birthday leave.
- 100% paid parental leave with structured reintegration support.
- Wellness programs including fitness access, mental health support, and therapy sessions.
- Home office setup reimbursement and flexible scheduling options.
- Strong learning culture with career development programs and internal mobility opportunities.
- Inclusive, global work environment focused on collaboration, wellbeing, and innovation.
Your email job alert is now active!
