Top Machine Learning Jobs in Sao Paulo

The Advanced Accelerator Program focuses on training engineers in either LLMs or MLOps, providing them with the skills to design, build, and maintain ML systems. Program graduates will master scalable ML solutions and apply software engineering best practices in production environments.

The VP of Technology, Data & AI is responsible for leading a team of data and AI engineers, shaping data strategies, overseeing data architecture, and driving innovative AI solutions. This role involves collaboration across teams to ensure project delivery aligning with business goals, while fostering a culture of innovation and excellence.

The Senior Product Manager for the AI Pricing Engine will define the product vision and strategy, develop a roadmap for pricing accuracy, collaborate with data science and engineering teams to build and integrate machine learning models, and lead cross-functional efforts to optimize pricing strategies and enhance customer experience.

The Senior Solutions Architect at OfferFit will work closely with the Sales team to educate enterprise customers about the AI product, conduct proofs-of-concept, and facilitate technical discussions. They will also lead workshops and collaborate with various functions to enhance product offerings while building strong relationships with stakeholders.

The Senior ML Backend Engineer will design, build, and maintain scalable backend systems for enterprise security products. Responsibilities include translating business goals into technical specifications, working with various architectures, writing code in Python and JavaScript/TypeScript, ensuring code quality with tests, and participating in code reviews. The position requires 5+ years of experience in production systems and knowledge of orchestration platforms and databases.

As a Senior Software Engineer on the ML Platform Engineering team, you’ll develop and expand core infrastructure for AI/ML products. Responsibilities include technical contributions in design, documentation, collaboration within a cross-functional team, and ownership of deployed services in AWS and Kubernetes.

As a Machine Learning Solutions Architect, you will design data solutions, extract data for analysis, define deployment strategies for models, and provide thought leadership on technology choices. You will implement infrastructure and ensure that data science models can be effectively utilized by businesses.

The DataOps/ML Engineer role involves developing high-quality applications, utilizing AWS services and machine learning tools. Responsibilities include automating deployment pipelines and implementing ML monitoring systems, while collaborating in a dynamic environment. Candidates should have strong coding experience and familiarity with various technologies in cloud and machine learning.