Senior Machine Learning Engineering Analyst – Artificial Intelligence

Itaú Unibanco

. Develop RAG and agent memory solutions for production environments .

Posted 9/29/2026full-timeSão Paulo • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Machine Learning and Deep Learning, with a strong focus on developing and optimizing Generative AI solutions. Proficient in building scalable context-retrieval pipelines and implementing engineering best practices, including CI/CD and IaC.

Highest-signal resume keywords

Machine LearningDeep LearningPyTorchTensorFlowCI/CD

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative AINeural NetworksEmbeddingsVector SearchAutomated TestingPythonObservabilityStatistical AnalysisExperimentationBenchmarking

Tools & Technologies

TerraformAWSAzureGCPDatadogGrafanaPrometheus

Industry Keywords

Distributed Systems ArchitectureSoftware Engineering Best PracticesRerankingBi-EncodersCross-EncodersKnowledge GraphsEntity ExtractionEntity Resolution

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformGrafanaPrometheusPythonPyTorchTensorflowTerraform

About the role

Key responsibilities & impact

Develop RAG and agent memory solutions for production environments
Optimize semantic search using embeddings and reranking techniques, such as bi-encoders and cross-encoders
Build and evolve context-retrieval pipelines focused on scalability, availability, and performance
Conduct experiments and benchmarks to evaluate and compare models
Develop solutions according to engineering best practices, including testing, CI/CD, IaC, and observability
Contribute to technical and architectural decisions related to the Generative AI platform
Work with Generative AI, Machine Learning, software engineering, and cloud technologies
Work across the full lifecycle, from model experimentation and evaluation to building robust production solutions
Make an impact on the bank’s digital products at scale

Requirements

What you’ll need

Strong knowledge of Machine Learning, Deep Learning, and neural networks
Experience with PyTorch and/or TensorFlow
Knowledge of generative model architectures, such as Transformers, Encoders, and Decoders
Experience with embeddings and vector search
Knowledge of distributed systems architecture and software engineering best practices
Experience with automated testing and Python/pytest
Knowledge of observability, including logs, metrics, and tracing
Experience with CI/CD, DevOps/DevSecOps, and IaC, such as Terraform
Experience with at least one cloud provider: AWS, Azure, or GCP
Experience with LangChain, LangGraph, or LlamaIndex is a plus
Knowledge of evaluating Generative AI applications and agents (evals) is a plus
Experience with Datadog, Grafana, or Prometheus is a plus
Knowledge of reranking, bi-encoders, and cross-encoders is a plus
Experience with experimentation, benchmarking, and statistical analysis is a plus
Experience with LLMs, SLMs, and embedding models is a plus
Knowledge of knowledge graphs, entity extraction, and entity resolution is a plus

Benefits

Comp & perks

Transportation allowance
Meal voucher (restaurants) / food allowance (supermarkets)
Medical plan (Fundação Saúde Itaú or Central Nacional Unimed)
Dental plan (Odontoprev or Interodonto)
Life insurance
Profit-sharing and results bonus (PLR), based on the bank’s results
Private pension plan
Exclusive discounts on our financial products
Extended maternity and paternity leave
Childcare / nanny allowance (for parents)
Education assistance
Wellhub or TotalPass
Access to Itaú Leisure Clubs (Guarapiranga / Itanhaém and São Sebastião)
Commitment to diversity and inclusion; applications from people with disabilities are encouraged