Top Machine Learning Jobs in Brasilia

The Advisory Solutions Consultant supports LATAM sales for Strategic and Enterprise accounts by aligning customer requirements with SailPoint solutions, providing technical expertise, and delivering product demonstrations.

Identify Brazilian species through images and audio, support biodiversity surveys, and train machine learning models by annotating data.

As an Applied AI Researcher, you will develop algorithms for diverse data modalities, collaborate on innovations, and lead research dissemination in GenAI.

The Senior Machine Learning Engineer will enhance Xometry's ML capabilities, develop models for cost prediction, lead technology evaluations, and collaborate on AI solutions.

Responsible for managing a team of cloud engineers, overseeing technical tasks, engaging with clients, mentoring team members, and ensuring technical accountability on projects.

As an AI Operations & Automation Specialist, you will optimize finance and HR operations through automation, AI implementation, and process improvement while ensuring data integrity and supporting various teams in the company.

Lead data science projects integrating expertise in statistics and machine learning to drive business value. Collaborate cross-functionally, ensure data quality, and mentor junior team members.

As an Analytics Engineer, you'll refine data, build models, enable self-service analytics, and collaborate with various teams to improve customer insights.

The Product Owner will manage the product backlog, translate business needs into user stories, ensure product alignment within Agile teams, and drive continuous improvement of product outcomes, especially in AI/data-driven products.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

The Senior Product Manager will own and drive the development of Kraken's Algorithmic Execution & Strategy Engine, focusing on execution algorithms, API specifications, and client engagement to optimize trading strategies.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The Data Scientist will lead data-driven decision-making, develop machine learning models, design automated pipelines, and improve product performance.

The Principal AI/ML Architect leads client engagements, advising on ML architecture and strategies, overseeing ML systems, and ensuring technical quality for diverse customer needs with a focus on AWS technologies.

Train and evaluate AI models for computer vision tasks, assess model accuracy, create training data annotations, and suggest improvements for visual data interpretation.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.

The AI/ML Engineering Manager will lead a team of ML engineers, manage client engagements, shape architecture, and drive pre-sales while ensuring team growth and performance.

The Data Engineer will design and maintain scalable data pipelines and support ML workflows, ensuring reliability and performance of data systems.

The Engineering Matcher connects clients with technical talent by analyzing resumes, conducting interviews, and maintaining a candidate pool while collaborating with stakeholders.

The Senior Machine Learning Engineer designs and maintains ML solutions, collaborates on data-driven projects, and mentors junior engineers.

Develop and evaluate scalable deep learning algorithms, collaborate on generative modeling, and improve data processing pipelines to enhance understanding of neural mechanisms.

Architect, build, and deploy low-latency, high-throughput ML systems across the full ML lifecycle: scalable feature pipelines, training/tuning of tree and deep models, production packaging/serving, MLOps automation, monitoring for drift, and rigorous A/B experimentation to drive business metrics.

As a Machine Learning Engineer/Data Scientist, you'll build and deploy ML solutions, collaborate with stakeholders, and analyze data, focusing on achieving measurable business impact.

Develop and maintain AI and ML algorithms, create data pipelines, collaborate with cross-functional teams, and implement solutions for business requirements.