Senior Machine Learning Engineer / MLOps (Stone)
Stone - Linkedin1 day ago
Remote, BrazilSenior
Responsibilities
- Act as the bridge between Data Science and production environments.
- Create, architect, and maintain efficient, scalable, and low-latency machine learning systems and pipelines.
- Design and document system architectures using the C4 Model and implement software engineering best practices.
- Create CI/CD pipelines for machine learning workflows.
- Manage the ML lifecycle, including experiment tracking, Feature Store governance, infrastructure as code, cost and compute optimization, and model quality and drift monitoring.
- Define batch and online serving strategies and create inference APIs using FastAPI and Databricks.
- Containerize ML applications with Docker and implement monitoring and alerts.
- Build scalable distributed and real-time data processing pipelines using PySpark, Spark SQL, and Apache Kafka.
Requirements
- Strong command of software engineering practices, including clean code, testing, design patterns, system design, architecture documentation, and ML CI/CD.
- Expertise in MLOps and the ML lifecycle, especially with Databricks, MLflow, Feature Store, Databricks Asset Bundles, model monitoring, and drift detection.
- Experience defining serving strategies, developing inference APIs, containerizing applications, and monitoring production systems.
- Experience building scalable distributed data pipelines with PySpark, Spark SQL, and streaming technologies such as Apache Kafka.
- Preferred: strong prior experience in Backend, DevOps, or SRE roles involving production microservices.
- Preferred: experience integrating and productizing LLMs and generative AI using OpenAI or open-source models.
- Preferred: experience with dbt, Delta Lake, and data modeling.
- Preferred: experience working across AWS, GCP, and Azure.
Benefits
- Fixed salary and variable compensation package, subject to role eligibility.
- Health and dental insurance with copay rules, plus 24/7 telemedicine access through Hospital Virtual Verde.
- Medication subsidy, meal and/or food allowance through Pluxee, childcare assistance, and assistance for children with disabilities.
- Life insurance, fuel or commuting allowance, and home-office allowance for hybrid or remote contracts.
- New-parent welcome kit, SESC partnership, education benefits through Studa and Stone Library, Acolhe360 emotional support, quick massage, and outpatient clinic access.
- Optional benefits include Wellhub, TotalPass, Pet Club, Flash, Férias&Co, transportation allowance, Allya, and educational partnerships.
Tech Stack
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