Machine Learning Engineer – Mid-level
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Job Description
Machine Learning Engineer responsible for developing and operating scalable ML solutions at Extractta. Collaborating with product, data, and engineering teams to deliver robust models.
Responsibilities:
- Design and implement ML pipelines (training, validation, deployment, and inference) with a focus on scalability and cost.
- Put models into production using MLOps practices (versioning, reproducibility, automation, and performance/drift monitoring).
- Build and maintain inference services (batch and/or real-time), APIs, and integrations with internal systems.
- Collaborate with data scientists, analysts, and product teams to translate business needs into solutions.
- Ensure quality (testing, code review, documentation), security, and engineering best practices.
- Monitor operational metrics and outcomes (SLA, latency, cost, accuracy, business impact).
Requirements:
- Hands-on experience deploying models to production (end-to-end).
- Strong programming skills (primarily Python) and software engineering fundamentals (APIs, testing, clean code).
- Knowledge of applied ML (classification, regression, ranking, NLP/LLMs when applicable) and validation best practices.
- Experience with data pipelines (SQL and/or orchestration) and integration with data platforms.
- Experience with cloud and managed services (primarily AWS) and containers (Docker).
- Familiarity with observability (logs, metrics, and tracing) and model monitoring.
- Diferentials
- Experience with Kubernetes and scalable inference architectures.
- Experience with MLOps tools (e.g., MLflow, feature stores, model registries) and CI/CD.
- Experience with NLP/LLMs, RAG (retrieval-augmented generation), and evaluation/observability of model-based applications.
- Knowledge of data/AI governance (LGPD, audit trails, explainability when required).
- Experience in the financial sector (risk, fraud, credit, customer behavior).
Benefits:
- Meal allowance and/or food voucher.
- Affiliation with Sesi and Sesc, providing access to health, wellness, and leisure services.
- Partnerships with educational institutions offering exclusive discounts on courses and educational programs.
- Opportunity for career growth within the company and participation in strategic projects.
- Opportunity to work at a rapidly growing company in the market.
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