15219 - Machine Learning Engineer – AI / Generative AI

Role: Machine Learning Engineer – AI / Generative AI

- Starting Date: Immediately
- Contract: CLT at UltraCon's Customer
- Work Location: São Paulo/SP @ Av. Paulista (hybrid: 3x/week - presence in the office is mandatory on Tuesdays, Wednesdays and Thursdays)
- Work Time: Business Hours
- Language: English Advanced

Position Overview
 
We are looking for an experienced Machine Learning Engineer with strong expertise in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) to design, develop, integrate, and deploy AI-driven solutions for real-world applications.

The professional will be responsible for building and optimizing machine learning models, developing applications powered by Large Language Models (LLMs), and implementing reliable AI/ML workflows. This role requires hands-on technical expertise, strong analytical capabilities, and the ability to translate business and technical requirements into practical AI solutions.

The ideal candidate combines software engineering and machine learning expertise with the ability to evaluate different technical approaches, solve complex problems independently, and collaborate with cross-functional teams.

Key Responsibilities
 
• Design, develop, test, and deploy Machine Learning and Artificial Intelligence solutions.
• Build, train, optimize, and maintain ML models and AI-powered applications.
• Develop and integrate Generative AI solutions leveraging Large Language Models (LLMs).
• Process and analyze structured and unstructured datasets for model development and evaluation.
• Develop and maintain data preprocessing, feature engineering, model training, validation, and inference workflows.
• Evaluate model accuracy, reliability, performance, and overall quality.
• Integrate AI/ML models into applications, services, and APIs.
• Assess and select appropriate AI/ML models, algorithms, and technical approaches based on business requirements.
• Collaborate with engineering, data, product, and business teams to translate requirements into practical AI solutions.
• Troubleshoot, optimize, and improve existing machine learning models and pipelines.
• Apply software engineering and machine learning development best practices throughout the solution lifecycle.

Required Skills
 
• Strong hands-on experience in Machine Learning and Artificial Intelligence.
• Practical experience designing and developing Generative AI solutions.
• Experience working with Large Language Models (LLMs).
• Strong programming skills in Python.
• Experience using machine learning frameworks and libraries.
• Solid knowledge of machine learning algorithms, model training, validation, and evaluation techniques.
• Experience with data preprocessing, data preparation, and feature engineering.
• Experience integrating AI/ML models into applications and services through APIs.
• Ability to evaluate different AI/ML approaches and select appropriate solutions for specific use cases.
• Strong practical experience developing AI/ML solutions beyond academic or experimental environments.
• Ability to develop AI/GenAI solutions that can be integrated into real-world applications.

Preferred Skills
 
• Experience with PyTorch, TensorFlow, or similar machine learning frameworks.
• Experience developing LLM-based applications using prompt engineering techniques.
• Knowledge of embeddings and vector-based retrieval techniques.
• Familiarity with Retrieval-Augmented Generation (RAG) architectures.
• Experience with cloud-based AI/ML platforms.
• Knowledge of MLOps practices, including model deployment, monitoring, and lifecycle management.
• Experience with containerization technologies and CI/CD practices.

Soft Skills and Professional Competencies
 
• Analytical Thinking: Ability to analyze complex technical challenges and identify appropriate AI/ML approaches.
• Problem-Solving: Strong ability to troubleshoot models, workflows, and technical issues.
• Autonomy: Ability to work independently on complex machine learning problems.
• Collaboration: Experience working effectively with engineering, data, product, and business teams.
• Communication: Ability to explain technical concepts and recommendations clearly to technical and non-technical stakeholders.
• Technical Decision-Making: Ability to evaluate alternative models and technical approaches based on specific requirements and use cases.

Resume Submission Guidelines
 
Please submit an updated resume in Word format, clearly highlighting your hands-on experience with Machine Learning, Artificial Intelligence, Generative AI, Large Language Models (LLMs), and Python. Include relevant projects involving model development, training, evaluation, and integration with applications or APIs. Experience with PyTorch, TensorFlow, RAG architectures, embeddings, cloud AI/ML platforms, and MLOps should be highlighted where applicable. For each relevant project, specify the company or project name, period of involvement, technical responsibilities, technologies used, and solutions delivered.

Further information will be given along the technical interview.