• Criar e desenvolver soluções financeiras (aplicativos web e móveis) de alta qualidade, focadas na experiência do usuário. • Atuar diretamente na análise e resolução de problemas complexos em produção (troubleshooting). • Participar ativamente de diagnósticos técnicos junto a clientes e áreas internas. • Trabalhar com integrações via APIs, webservices e sistemas distribuídos. • Apoiar na definição de arquitetura e soluções técnicas para novos projetos. • Garantir qualidade técnica das entregas, incluindo revisão de código e boas práticas. • Apoiar times de QA, requisitos e implantação na validação de cenários técnicos. • Atuar em situações críticas que exigem resposta rápida e análise aprofundada.

• Ability to work autonomously to resolve technical problems. • Strong communication and collaboration with cross-functional teams. • Analytical skills for investigating and solving problems. • Proactive in identifying improvements. • Develop and evolve backend solutions based on microservices, with attention to quality, security and performance. • Implement and maintain REST APIs. • Participate in analysis and resolution of incidents in production environments. • Refactor system features to address technical debt and improve performance. • Work closely with technical areas, maintaining an integrated view of solutions. • Maintenance of legacy systems.

• Design and implement vehicle routing and scheduling algorithms using OR-Tools to generate optimal field assignments • Develop clustering algorithms to group workloads geographically and minimize travel time/cost • Implement constraint models (capacity, time windows, skills, priorities, survey rules) within the optimizer • Integrate the optimizer with the Mojo control system APIs for job intake, execution, and results publishing • Build batch and real-time optimization modes to support both scheduled and on-demand routing • Refactor optimizer components into modular, extensible strategy interfaces for new routing heuristics • Implement data preprocessing pipelines to normalize locations, distances, and travel matrices • Develop automated test harnesses validating solution correctness against known datasets and constraints • Implement “solution quality” scoring metrics (distance, balance, SLA adherence, cost) to evaluate goodness of routes • Create regression benchmarks comparing new algorithm performance vs. baseline outputs • Add parallel processing and scaling support to handle large route sets and high agent counts • Instrument services with logging and metrics to track runtime, solver performance, and solution quality • Package optimizer services for CI/CD deployment with reproducible builds and environment configs • Document routing logic, constraints, integration points, and operational runbooks • Provide production support, tuning, and continuous improvement of optimization heuristics and performance

Role Description We invite a skilled AI Engineer to join our team in building GPU-accelerated video analytics for real-time safety monitoring across large fleets and industrial environments. In this role, you’ll help design and optimize pipelines that detect and track actionable safety events in high-volume video streams. You’ll work on real-world systems that make an impact, collaborating with engineering and product teams to deliver reliable, high-performance solutions. Qualifications - 7+ years of software engineering experience with strong backend skills - 3+ years of experience shipping computer vision solutions to production - Strong Python proficiency - Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations - Hands-on experience with YOLO/Ultralytics or similar object detection frameworks - Experience detecting, labeling, and tracking objects in video - Solid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation - Experience with GPU inference optimization (batching, stride, TensorRT, CUDA, quantization, throughput tuning) - Ability to communicate and collaborate effectively with engineering and product teams - Upper-Intermediate+ English level Requirements - Experience with Azure Event Hub, Blob Storage, Application Insights, or similar (desirable) - Familiarity with Docker, cloud deployments, and production monitoring systems (desirable) - Experience in temporal/sequence analysis for event detection (desirable) - Experience with video analytics in safety, compliance, or industrial/transportation environments (desirable) Key Responsibilities - Develop and maintain robust backend solutions that process video data and deliver actionable insights using pre-trained computer vision models. - Develop and optimize GPU-accelerated video inference pipelines for real-time processing. - Implement, evaluate, and improve object detection models (YOLO or similar). - Build temporal smoothing and tracking logic for safety event detection. - Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools. - Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services. - Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs. - Collaborate on dataset curation, labeling, model training, validation, and experiment tracking. - Support containerized deployments (Docker) and assist with monitoring and scaling production workload. Next Steps - Submit a CV in English - Intro call with a Recruiter - Internal interview - Client interview - Offer