Machine Learning Engineer — Specialist

Title: Machine Learning Engineer — Specialist

Location: Alphaville – Barueri, São Paulo

Work Model: Remote

MAIN RESPONSIBILITIES

• Design complex systems to train and serve machine learning models following industry best practices.
• Define projects and scope for engineering teams, guiding them to successful completion.
• Develop, identify, and report intellectual property through patent applications, invention disclosures, white papers, and presentations.
• Demonstrate effective, respectful, and honest communication when collaborating with executives, clients, and peers across organizations.
• Contribute to all product development phases from Analysis and Design to successful Deployment.
• Fulfill company initiatives and prioritize projects supporting long-term technical vision.
• Collaborate with product teams, architects, and stakeholders to understand opportunities and constraints of AI, ML, and data engineering.
• Participate in peer design reviews and code reviews.
• Drive innovations that add value to the IT organization; elevate peer performance through coaching, mentoring, and promoting best practices (may act as team lead).

ROLE OVERVIEW

FUNCTION: TECHNOLOGY DEVELOPMENT & CUSTOMER SERVICE

• Responsible for the conception, development, and implementation of short- and long-term information technology solutions. Reviews technology requirements and business processes; codes, tests, debugs, and implements software and machine learning solutions to deliver technology change across the business.

KEY CORE COMPETENCIES

• Big Data Analysis: Deep domain expertise to build high-impact big data machine learning solutions.
• Collaboration: Engages data scientists, product managers, and executives to present technical solutions and integrate ML models into larger systems.
• Cloud Computing: Proficiency in data architecture, data strategy, orchestration, ETL, data modeling, parallel processing, and performance tuning.
• Application Development: Conducts code reviews for quality and performance, optimizing critical codebase areas and establishing SDLC best practices.
• Artificial Intelligence: Designs scalable ML architectures and defines technical roadmaps aligned with organizational goals.
• Technical Leadership: Leads MLE/DS teams, sets clear goals, provides guidance, and fosters a collaborative environment.
• Mathematics & Research: Reads and understands cutting-edge ML research papers and applies innovative techniques to real-world challenges.

EXPERIENCE & QUALIFICATIONS

• Bachelor's degree in a STEM field (Science, Technology, Engineering, Math) or equivalent experience; Master's degree and AI/ML coursework strongly preferred.
• 5+ years of related work experience, including proven experience leading MLE, Data Science, SDE, or DevOps teams.
• Hands-on experience in end-to-end ML model development from ideation to production deployment, ensuring reliability and scalability.
• Cloud certification is strongly preferred.