Especialista em Ciência de Dados (Machine Learning)
Tasks
- Conduct build vs buy and platform vs service architecture trade offs
- Define ML IA technical vision and roadmap
- Design and implement data and ML pipelines
- Develop and orchestrate agents and multi agents systems
- Implement ML IA guardrails and security privacy practices
- Measure value and scale innovation with governance
- Prioritize solutions by impact risk and feasibility
- Serve as technical lead for ML IA and data
Perks/Benefits
- 24x7 telemedicine
- Childcare assistance
- Dental insurance
- Education assistance
- Extended maternity leave
- Extended paternity leave
- Flexible work hours
- Health insurance
- Home-office allowance
- Internal guilds and study groups
- Life insurance
- Meal and food allowance
- Online therapy
- Phone plan allowance
- Profit sharing and results bonus
- Transport allowance
- Wellhub
- Work from anywhere
Skills/Tech-stack
.Net Core | AWS | Access Control | Amazon Kinesis | Amazon SageMaker | Apache Spark | Batch Processing | Big Data | CI/CD | Caching | DLP | Data Modeling | Drift Detection | ECS | EKS | Experiment tracking | Faiss | FinOps | Git | Glue | Kafka | LGPD | LLM Evaluation | LLMOps | Lambda | MLOps | Model Registry | Monitoring | NoSQL Databases | NumPy | Observability | OpenSearch | PGVector | Pandas | Pinecone | Privacy | Prompt injection | Prompt injection mitigation | Prompting | PyTorch | Python | RAG | Relational databases | S3 | SQL | Scikit-learn | Security | Step Functions | Streaming | TensorFlow | Vector Databases
Education
N/A
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