Machine Learning Engineer Especialista II (Diretoria de Dados - Consumidor)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer Especialista II (Diretoria de Dados - Consumidor) based in Brazil.

This role offers the opportunity to design and scale advanced machine learning solutions that transform consumer data into impactful business insights. You will work at the intersection of AI, data engineering, and cloud technologies within a dynamic and innovation-driven environment. The position focuses on building end-to-end ML pipelines, improving model performance, and enabling data products that support strategic decisions. You will contribute to the evolution of MLOps practices, AI architectures, and generative AI solutions. Working with multidisciplinary teams, you will help prototype ideas, validate concepts, and deliver scalable AI capabilities. The role requires strong technical expertise, curiosity, and the ability to turn complex challenges into practical solutions. This is an opportunity to influence the future of data-driven experiences through cutting-edge technology.

Accountabilities:: The Machine Learning Engineer will be responsible for developing, optimizing, and maintaining advanced data and AI solutions, ensuring reliability, scalability, and business impact. The role combines technical leadership, engineering excellence, and collaboration with different stakeholders to deliver innovative machine learning products.

Build end-to-end Machine Learning pipelines, including data preparation, code optimization, automated model training, and prediction workflows.

Monitor model quality, efficiency, costs, and usage metrics for data products and AI solutions.

Provide technical leadership in MLOps processes, establishing development, deployment, and maintenance best practices.

Design and implement cloud-based architectures for AI and data solutions using platforms such as GCP, AWS, or Azure.

Develop data pipelines incorporating Generative AI models, including workflows for transforming unstructured data into structured information.

Create pilots and prototypes with business teams to validate concepts and demonstrate value.

Establish documentation practices for processes, APIs, technical decisions, and postmortems.

Collaborate with cross-functional teams to identify opportunities where machine learning can solve complex business challenges.

Requirements:

The ideal candidate combines strong machine learning expertise with software engineering skills and the ability to work independently in a fast-changing technology environment.

Solid knowledge of Machine Learning concepts, including supervised learning, unsupervised learning, and Generative AI.

Advanced programming skills in Python and SQL.

Strong understanding of the machine learning lifecycle, including model development, deployment, monitoring, and maintenance.

Experience designing ML architectures and workflows for batch processing solutions.

Professional experience with cloud services, containers, and Docker environments.

Experience building data and ML pipelines using industry tools such as Airflow, Kubeflow, or Vertex AI.

Knowledge of AI agent frameworks and modern AI development approaches.

Familiarity with machine learning, big data, or computer systems concepts through education or professional experience.

Ability to quickly learn new technologies and apply creative approaches to solve problems.

Experience with AI-assisted software development tools such as GitHub Copilot or Claude Code.

Strong analytical thinking and communication skills, with the ability to explain complex technical concepts clearly.

Experience documenting technical processes, APIs, and engineering practices.

Preferred qualifications include:

Experience developing recommendation systems.

Knowledge of secure software development practices, OWASP principles, and responsible AI/data usage.

Experience with large-scale web scraping solutions.

Familiarity with distributed data processing frameworks such as Apache Spark or Apache Beam.

Advanced academic background such as a Master’s or PhD in a related field.

Benefits:

Fully remote work model with flexibility to support work-life balance.

Medical and dental insurance coverage.

Medication assistance and healthcare support programs.

Free psychotherapy sessions, telemedicine, and medical second-opinion services.

Flu vaccination programs and wellness initiatives.

Meal allowance or local restaurant benefits, depending on work model.

Food allowance and special holiday food benefits.

Fitness and wellness partnerships with gyms and activity studios.

Home office support for remote and hybrid employees.

Pet health plan options.

Birthday day off.

Discounts on products and exclusive employee partnerships.

Family support benefits, including childcare assistance and extended parental leave.

Educational support programs and resources for professional development.

Life insurance, private pension plan, and financial support programs.

Transportation assistance and parking support where applicable.

Opportunities to work with innovative AI, data, and technology initiatives in a collaborative environment

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1