Senior MLOps Engineer – Real-Time ML

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

📋 Description

• Spearhead the architectural design of the real-time machine learning platform, assessing options and guiding technical choices.

• Provide the platform as a service, complete with standards, interfaces, and documentation that empower data science and product teams to autonomously define, deploy, and utilize features and models.

• Develop and enhance the online and offline feature store, incorporating cataloged metadata.

• Create and refine model registry and versioning functionalities.

• Construct and advance real-time inference capabilities.

• Establish and improve production model monitoring.

• Guarantee consistency between features utilized for training and inference, employing the same logic in both batch and streaming contexts.

• Collaborate with engineering teams to define requirements pertinent to event flows.

• Integrate the platform with AWS machine learning services, leveraging Amazon SageMaker for feature storage, model registry, and real-time inference.

• Organize the operational framework of the platform and production models alongside Cloud and Data Platform teams, applying Infrastructure as Code (IaC), standards, and runbooks.

• Ensure latency, availability, and scalability through Service Level Objectives (SLOs) and observability.

• Record technical decisions, standards, and operational procedures.

⛳️ Requirements

• Proven experience in deploying real-time machine learning models, event-triggered inference, and meeting low-latency demands.

• Background in delivering platforms as a service, with self-service architectural standards, documentation, and interfaces that allow science and product teams to operate independently.

• Experience in developing online and offline Feature Stores with cataloged metadata.

• Familiarity with maintaining consistency between training and inference processes.

• Hands-on experience in structuring model registries and versioning, such as with MLflow.

• Experience in monitoring models in a production environment.

• Background in building data and machine learning platforms on AWS, preferably utilizing Amazon SageMaker or similar services.

• Advanced skills in Python and SQL.

• Advanced expertise in Terraform (IaC).

• Experience in automating deployments via CI/CD pipelines.

• Knowledge of production observability practices.

• Nice to have: experience with financial products and real-time decision-making.

• Nice to have: familiarity with Kafka, Kinesis, CDC, AWS DMS, or MSK.

• Nice to have: experience within the Databricks ecosystem.

• Nice to have: understanding of Brazil’s LGPD, Central Bank of Brazil (BACEN) regulations, and SOX requirements.

🏝️ Benefits

• Medical and dental insurance without copayments.

• Life insurance coverage.

• Assistance with prescription medications.

• Fitness allowance provided.

• Four complimentary therapy or nutritionist sessions monthly.

• Quick massage services at the headquarters.

• Flexible meal benefits available on a Visa card.

• Complimentary meals at headquarters.

• Childcare support available.

• Parental support program in place.

• Extended maternity and paternity leave offered.

• Access to an in-house training platform.

• Education assistance covering 70% of undergraduate tuition, language courses, and other educational materials.

• Home office allowance provided.

• Work equipment supplied.

• Home office furniture allowance available.

• Partnership with WOBA for coworking space access across Brazil.

• Day off during birthday month.

• Happy hour allowance offered.

• Referral bonus for introducing new hires.

• Annual goal-based bonus available.

• Stock option plan offered.

• No formal dress code policy in effect.