Staff ML Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Collaborate with ML researchers in generative AI teams to pinpoint bottlenecks and enhance the speed, scalability, and reliability of research iterations.

• Design, construct, and uphold reusable research infrastructure, workflows, models, interfaces, and automation for experimentation, training, evaluation, data processing, and model packaging.

• Facilitate reproducible experiments through consistent environments, dependency management, artifact and model versioning, configuration, observability, and CI/CD practices.

• Support scalable ML workloads that involve large datasets, GPU clusters, distributed computing, and various interconnected models, services, and algorithm components.

• Provide practical research-support capabilities that align with the architecture and roadmap of the core ML platform.

• Act as a technical liaison between researchers and the ML platform team by translating challenges into clear requirements, validating capabilities, and assisting in the adoption of the shared platform.

• Work collaboratively to enhance the transition from research to product by simplifying the reproduction, integration, and testing of results.

• Contribute to the establishment of shared ML engineering standards and architecture, promoting engineering practices through hands-on collaboration, technical guidance, and knowledge sharing.

• Assess and implement technologies that enhance the speed, reliability, scalability, and cost-effectiveness of research.

⛳️ Requirements

• Demonstrated experience in building reusable infrastructure, tools, or developer platforms for multiple engineers or researchers.

• Strong expertise in Python and Linux.

• Practical experience with Docker, Kubernetes, CI/CD pipelines, AWS, and Infrastructure as Code, such as Terraform.

• Comprehensive understanding of the complete ML lifecycle, including data preparation, experimentation, training, evaluation, model and artifact management, packaging, deployment, and monitoring.

• Experience with compute-intensive or distributed workloads, including diagnosing reliability, performance, resource, and cost-related bottlenecks.

• Practical knowledge of modern ML frameworks, such as PyTorch.

• Capability to navigate ambiguous and evolving requirements and translate them into reusable engineering solutions.

• Excellent communication and cross-functional collaboration abilities across research, engineering, and platform teams.

• Proficient in English—conversational, written, and reading skills required.

• Commitment to diversity, inclusion, and accessibility.

• A natural curiosity.

• A collaborative mindset.

• A structured and action-oriented approach.

• Comfortable working in uncertain and early-stage environments.

• Focused on impact.

• Nice to have: experience in language modeling, language translation, computer vision, multimodal or generative AI, robotics, and autonomous systems.

• Nice to have: experience in scaling GPU clusters, distributed computing, and large-scale data processing.

• Nice to have: experience in developing researcher-facing ML platforms and self-service experimentation environments.

• Nice to have: experience assisting research teams in migrating to or adopting a shared ML platform.

• Nice to have: knowledge of inference optimization techniques, such as custom GPU kernels.

🏝️ Benefits

• CLT employment contract: Security and all legally guaranteed employment rights from day one.

• Caju Benefits Card (R$1,160.00): Flexibility to use your balance as you prefer—for meals, groceries, home office, culture, and transportation.

• Remote work from anywhere in Brazil.

• SulAmérica Health Insurance.

• SulAmérica Dental Insurance.

• SulAmérica Life Insurance.

• Online specialist consultations through Conexa Saúde telemedicine.

• Wellhub.

• Extended year-end break.

• Birthday day off.

• Extended parental leave.

• Ongoing professional development through LinkedIn Learning.

• Annual stipend for courses and professional training.

• University partnerships.

• Brazilian Sign Language (Libras) training.

• English Pass.

• Work equipment shipped as part of the onboarding kit.