• Collaborate with cross-functional teams to assist in the design and productionization of machine learning, ML ops, traditional AI, LLMs, and agentic AI solutions. • Support the implementation of application integrations to leverage newly built machine learning, ML ops, traditional AI, LLMs, and agentic AI products. • Assist in building solutions that improve the delivery speed and scalability of data and product pipelines. • Under minimal supervision, work on leveraging managed and serverless cloud offerings for application solutions and data engineering pipelines. • Support client-facing teams by preparing technical documentation and assisting in project communications. • Stay up to date with the latest advancements in data science, machine learning, and AI technologies.

• Lead and drive ambitious research initiatives that advance the state of the art in computer vision, multimodal understanding, and visual generation. • Develop novel models, algorithms, and training methodologies for challenging vision problems such as image understanding, video understanding, visual search, scene representation, segmentation, detection, generation, and multimodal reasoning. • Translate cutting-edge research into practical model improvements that can shape product direction and unlock new user experiences. • Design, implement, train, and optimize large-scale vision and multimodal foundation models across diverse datasets and tasks. • Partner closely with applied scientists, ML engineers, and product teams to move research from exploration to production-ready systems. • Set technical direction for high-impact research areas, identifying promising bets and influencing longer-term strategy for vision and multimodal AI. • Mentor other scientists and engineers, raise the quality bar for research, and help build a strong scientific culture across the team. • Stay at the forefront of research in computer vision, multimodal learning, generative modeling, and foundation models, and apply emerging techniques to real-world problems.

• Own the end-to-peer validation for existing algorithms • Visually validate data from cart collects for accuracy • Curate training examples to improve model performance • Utilize AI generative algorithms to create diversified training images • Set up tooling and scripts to handle data needs • Establish a semi-automated process to identify and leverage failure cases • Compare system production output against ground truth • Develop and maintain simple scripts to parse system logs

Become an EXpert as a Machine Learning Engineer. At EX Squared LATAM, we collaborate with global clients to build innovative digital solutions that drive real business impact. We are currently looking for a Machine Learning Engineer to join our team and support the development of advanced ML and GenAI solutions for one of our clients. This role offers the opportunity to work on cutting-edge technologies, including LLM evaluation frameworks, ML infrastructure, and Agentic AI systems, within a highly collaborative and fast-paced environment. What You’ll Do - Design and implement scalable ML infrastructure to support model development and deployment - Develop and maintain evaluation frameworks for Large Language Models (LLMs), including RAG-based systems - Evaluate model performance using tools such as RAGAS, DeepEval, or similar frameworks - Contribute to the development of GenAI and Agentic AI solutions - Build and enhance monitoring systems for ML models in production environments - Collaborate with cross-functional teams including data scientists, engineers, and product stakeholders - Apply best practices in model versioning, testing, and deployment pipelines - Optimize performance, scalability, and cost efficiency in cloud environments What You’ll Bring - 5+ years of strong experience with Python for machine learning and backend development - Hands-on experience with ML infrastructure and model deployment pipelines - Experience evaluating LLMs using frameworks such as RAGAS, DeepEval, or similar - Solid understanding of GenAI concepts, including LLMs and Agentic AI systems - Experience working with Retrieval-Augmented Generation (RAG) architectures - Proficiency in cloud platforms such as AWS, GCP, or Azure - Familiarity with monitoring and observability tools for ML systems - Ability to work independently in a remote, distributed environment - Advanced English level 🌎 Why Join EX Squared? At EX Squared, we are a team of passionate technologists across LATAM, building impactful solutions for global clients. We foster a collaborative, inclusive, and innovation-driven culture where continuous learning and professional growth are at the core of everything we do. What We Offer - Competitive compensation in USD - 100% remote work in LATAM - Access to continuous learning and development programs - A collaborative and multicultural work environment - Opportunities to work on cutting-edge technologies and global projects #LI-REMOTE