Senior Machine Learning Engineer

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

📋 Description

• Take ownership of the entire model lifecycle — encompassing feature engineering, training, validation, registration, and deployment.

• Oversee models in production and spearhead retraining efforts when performance decline or drift is detected.

• Develop and enhance CI/CD pipelines that facilitate the promotion of models and workflows across development, staging, and production settings.

• Automate and operationalize model and agent evaluation pipelines to support Data Science initiatives.

• Create and sustain reusable internal metrics packages for standardized experimental procedures.

• Manage the infrastructure required for fine-tuning language models.

• Administer the AI Gateway, which includes model routing, rate limiting, and cost control and attribution.

• Ensure that feature, experiment, and model governance adheres to Afya's policies.

• Act as the technical liaison between Data Science, AI Engineering, Data Engineering, and SRE.

• Implement scalability, security, and cost-efficiency practices within the ML/AI infrastructure.

⛳️ Requirements

• Proficient in Databricks as the primary platform, acting as a technical authority in Model Serving, Unity Catalog, and Asset Bundles, along with MLflow for model registration, versioning, and evaluation.

• Comparable experience with SageMaker, Vertex AI, or Azure ML is also appreciated, coupled with a readiness to enhance expertise in Databricks.

• Advanced skills in Python, SQL, and Apache Spark / PySpark, applied to production Machine Learning pipelines (e.g., scikit-learn, XGBoost).

• Familiarity with CI/CD and infrastructure as code for promoting models and pipelines across development, staging, and production environments: GitHub Actions, Terraform (or equivalent IaC), cloud platforms (Azure, AWS, or GCP), and secrets management.

• Experience in production model operations: including version promotion and rollback, performance and cost monitoring, drift detection, and responding to endpoint incidents.

• Ability to interpret statistical evaluation results to decide on version promotion or rollback, ensuring governance of experiments, model versions, and inference data.

• Exposure to at least one LLMOps domain: AI Gateway, evaluation pipeline automation and reusable internal metrics packages, or LLM fine-tuning infrastructure.

• Exhibit senior technical leadership without people management responsibilities, including architecture design, negotiation of technical contracts, and mentoring mid-level engineers.

• Possess a completed higher education degree or a technology degree in Computer Science, Systems Analysis and Development, Engineering, Information Systems, Statistics, Mathematics, or a related field.

• Proficient in advanced technical English for reading documentation, release notes, and academic papers.

• Demonstrated experience in Machine Learning Engineering / MLOps, with a proven track record in supporting models in production: automated training, validation, promotion, deployment, monitoring, and retraining.

🏝️ Benefits

• Meal / food allowance.

• Flexible working hours and arrangements (for remote positions).

• Transportation allowance (for hybrid or on-site positions).

• Profit-sharing bonus.

• Flexible benefits: a flexible allowance via Flash Card for personal use.

• Gympass / Wellhub.

• Psicologia Viva (online platform for consultations with psychologists and nutritionists).

• Health and dental insurance.

• Life insurance.

• Extended parental leave (up to 6 months for mothers and 20 days for fathers).

• Rede D'Or: support and critical health information for mothers and babies through a network of accredited nurses.

• Birthday Day Off (one day off to celebrate your birthday or at any time during your birthday month).

• Access to a platform offering a variety of courses to enhance your knowledge (UCA).

• Language academy (AIA).

• Leadership development program.

• Discounts on undergraduate and graduate courses at Afya educational units.

• Premium subscription to Afya iClinic and Afya Whitebook (an additional benefit for physician professors).