IA e machine learning · Não informado
Mid Level Machine Learning Engineer
BEESCampinas, São Paulo, Brazil
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A vaga é para Mid Level Machine Learning Engineer na BEES. O modelo informado é não informado; localidade: Campinas, São Paulo, Brazil. Practical experience with ML platform components (e.g., feature pipelines, model registries, training and inference workflows). Experience with Kubernetes, Databricks, Terraform, Azure DevOps (Git), Azure Cloud, and ML frameworks/libraries such as Scikit-learn, PyTorch, TensorFlow, ONNX, and serving tools (BentoML, Kedro, Seldon, KServe, Triton Inference Server…
Resumo automático baseado somente nas informações publicadas pela empresa.
Sinais da vaga
O que mais pesa no anúncio
Uma leitura objetiva dos conhecimentos e níveis mais relevantes para esta oportunidade.
IA e automação
Muito alta · 5/5
No título da vaga
Senioridade · Pleno
Muito alta · 5/5
Nível indicado no título
Cloud e DevOps
Média · 3/5
Na descrição · 6 menções
Growth
Média · 3/5
Na descrição · 3 menções
Escala de 1 a 5. Mede presença e posição no anúncio; não mede sua chance de contratação.
Descrição completa
Contexto da oportunidadeAbrirFechar
About BEES
At BEES, our ambition is – and always will be – to put customers at the heart of everything we do, making their lives easier and their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and medium-sized retailers, unlocking new growth opportunities for all.
What you'll doAbrirFechar
Implement and extend ML platform capabilities (training jobs, inference services, batch and online serving) following team architecture, standards, and best practices.
Develop and maintain components of the ML model development workflow (project structure, experimentation, versioning, reproducibility) to improve consistency and reuse across teams.
Build and operate observability for models in training and production—monitoring, logging, and alerting for performance, quality, and drift—in collaboration with platform and SRE partners.
Support optimized model deployments (scaling, resource allocation, inference tuning) to meet cost, quality, and SLA targets.
Troubleshoot pipeline and serving issues, document solutions, and share learnings with the team.
What you'll need:
Bachelor’s degree in computer science, engineering, mathematics, or another quantitative field.
Practical experience with ML platform components (e.g., feature pipelines, model registries, training and inference workflows).
Solid software engineering fundamentals: clean code, testing, CI/CD, and maintainable system design.
Python, PySpark, and SQL. Exposure to Java is a plus.
Experience with Kubernetes, Databricks, Terraform, Azure DevOps (Git), Azure Cloud, and ML frameworks/libraries such as Scikit-learn, PyTorch, TensorFlow, ONNX, and serving tools (BentoML, Kedro, Seldon, KServe, Triton Inference Server, etc.).
Comfort collaborating across teams, communicating technical tradeoffs clearly, and learning from senior engineers on architecture and platform decisions.
What We Offer:
Performance based bonus*
Attendance Bonus*
Private pension plan
Meal Allowance
Casual office and dress code
Days off*
Health, dental, and life insurance
Medicines discounts
WellHub partnership
Childcare subsidies
Discounts on Ambev products*
Clube Ben partnership
Scholarship*
School materials assurance
Language and training platforms
Transport allowance
*Rules applied
Equal Opportunity & Affirmative Action:
ABI Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics.
The following fields are optional, but anticipate the information for your registration*.
Remember: your data will never be used as elimination criteria in selection processes. With them, ABI Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company.
For more information: www.bees.com and www.abinbev.com