Senior AI Engineering Analyst

Inmetrics

. Provide technical leadership in the development of advanced artificial intelligence algorithms and solutions.

Posted 10/22/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing machine learning and artificial intelligence algorithms, with a strong focus on MLOps, data processing, and integration within complex systems. Proven ability to lead technical teams, ensure model governance, and deliver scalable AI solutions.

Highest-signal resume keywords

Machine Learning AlgorithmsDeep Learning ModelsMLOps PracticesPython ProgrammingTensorFlow Framework

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningArtificial IntelligenceData ProcessingFeature EngineeringStatistical AnalysisModel ValidationAPI DevelopmentCloud ComputingData Engineering

Soft Skills

Analytical ThinkingComplex Problem-SolvingStrong CommunicationCollaborative ApproachProactive Mindset

Tools & Technologies

TensorFlowPyTorchScikit-learnDockerKubernetesAWSAzureGoogle Cloud PlatformGitCI/CD

Industry Keywords

Microservices ArchitectureREST APIsModel Lifecycle ManagementContinuous IntegrationTechnical Leadership

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaKubernetesNoSQLPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Provide technical leadership in the development of advanced artificial intelligence algorithms and solutions.
Provide technical leadership in the design, coding, and optimization of machine learning and deep learning models.
Define data processing, analysis, and usage strategies to create scalable AI solutions.
Ensure the integration of models with complex systems and pipelines.
Provide technical guidance to the team on the selection of frameworks, libraries, and best practices.
Ensure the validation, monitoring, and governance of models in production.
Design, develop, test, and maintain machine learning solutions for production environments.
Build data pipelines for data collection, processing, model training, validation, and monitoring.
Develop, optimize, and implement machine learning and artificial intelligence algorithms.
Deploy models to production using MLOps, automation, and continuous integration practices.
Monitor the performance, accuracy, availability, and efficiency of models in production.
Collaborate with Product, Data Engineering, Data Science, and Architecture teams.
Perform data analysis and preparation, feature engineering, and continuous model improvement.
Develop APIs and services to make AI and ML models available to applications and users.
Ensure the quality, security, scalability, and governance of the solutions developed.
Document processes, architectures, and technical procedures.
Support the sharing of technical knowledge and best practices within the team.
Participate in architectural decisions and the company's technological evolution.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Mathematics, Statistics, or a related field.
Experience developing software using Python, Java, or an equivalent programming language.
Solid knowledge of machine learning, deep learning, and artificial intelligence algorithms.
Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
Knowledge of statistics, probability, and mathematical modeling.
Experience with SQL and NoSQL databases.
Knowledge of microservices architecture and REST APIs.
Experience with Docker, Kubernetes, and containerization tools.
Experience working in cloud computing environments such as AWS, Azure, or Google Cloud Platform.
Knowledge of Git, CI/CD, and DevOps practices.
Experience with MLOps, monitoring, and model lifecycle management.
Knowledge of data processing and data engineering.
Analytical thinking and complex problem-solving skills.
Strong communication skills and the ability to explain technical concepts to diverse audiences.
Collaborative approach and experience working in multidisciplinary teams.
Proactive mindset and strong sense of ownership.
Ability to learn continuously and adapt to new technologies.
Results-oriented approach and focus on generating business value.

Benefits

Comp & perks

Bradesco health insurance (30% copayment)
Bradesco dental insurance (no employee contribution)
Life insurance
Wellhub (formerly Gympass)
Childcare assistance
Assistance for children with special needs
Payroll-deducted loan
Private pension plan
Pet care plan
SESC benefits
Conexa telemedicine
Expense allowance
Meal and food allowance
Multi-benefit card
Health insurance upgrade
Extended maternity and paternity leave
INMaterna Program: support program for expectant mothers
Birth gift basket and the book “It Happened When I Was Born”
Professional development: courses available through the internal university
100% remote or hybrid work, depending on project requirements