Jobs at EVB

Complete and review Salesforce workflows, manage CRM records, create reports and dashboards, use Flow automation, document processes, and provide feedback to help train AI systems. The role requires strong hands-on Salesforce experience, accurate data management, clear communication, and attention to detail. Salesforce certifications are beneficial but not required.

Reviews, evaluates, annotates, and edits written content for clarity, accuracy, grammar, structure, tone, and human-like quality. Provides constructive editorial feedback and written recommendations to improve AI training datasets. Collaborates remotely with project coordinators and specialists, completes assignments on schedule, and maintains consistent, high-quality deliverables.

Develop and improve open-source software using multiple programming languages. Responsibilities include feature development, bug resolution, legacy-code refactoring, performance optimization, code validation, competitive programming, peer collaboration, documentation, and technical writing. The role is remote and supports AI training projects, but no prior AI experience is required.

Build and deploy AI systems for leading labs and enterprise partners. Responsibilities include designing data intelligence platforms, ML and evaluation pipelines, taxonomies, labeling workflows, LLM applications, multi-agent and RAG systems, inference infrastructure, and human-in-the-loop workflows. The engineer will translate ambiguous research needs into production systems, manage full technical lifecycles, and collaborate directly with researchers, founders, and strategic partners.

Create reinforcement learning environments and golden reference solutions for AI software-engineering tasks. Develop code samples, debug complex defects, implement features, refactor legacy systems, optimize performance, document technical reasoning, and review peer submissions. Work may involve Python, Java, Rust, Go, C++, or TypeScript. The role is remote, part-time contract work with output-based compensation and rapid onboarding.

Reviews videos of robotic arms, identifies key actions and outcomes, and applies detailed grading guidelines to annotate events. Uses video annotation platforms to create structured datasets, collaborates with trainers to resolve ambiguities, documents findings, communicates progress, and participates in quality reviews. Strong attention to detail, organization, communication, and accuracy are essential. Experience with video annotation, AI training, machine learning data preparation, or robotics is preferred.

Design, develop, evaluate, and refine machine learning models using Python and leading ML frameworks. Analyze datasets with MongoDB, build preprocessing and data pipelines, tune hyperparameters, benchmark model performance, document experiments, and provide data-driven recommendations. Collaborate remotely with cross-functional contributors to improve and operationalize models in cloud or enterprise environments.