machine learning engineer for geospatial intelligence
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вакансия
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254 969 ₽
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описание
Nearmap provides property intelligence through aerial imagery, AI-driven analytics, and geospatial tools for people who plan, build, insure, and govern built environments.
задачи
Execute software engineering tasks supporting end-to-end machine learning operations and scaling workflows for large data and distributed systems;
Design, build, and maintain MLOps systems, including microservices, queuing systems, APIs, and orchestration workflows using Python, Kubernetes, Kafka, and modern database systems;
Implement observability tools such as Prometheus and Grafana to ensure reliability, performance, and visibility of ML systems in production;
Collaborate with data scientists and machine learning engineers to streamline workflows for LLM, generative AI, and Agentic AI development and deployment;
Review architecture and implementation plans for alignment with organizational goals, scalability, and best practices;
Mentor junior and mid-level engineers and foster collaboration, innovation, and operational excellence.
требования
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field;
5+ Years of professional experience in MLOps, DevOps, or Software Engineering, focused on building scalable and reliable software systems;
Proficiency in Python and Linux, with strong knowledge of scalable distributed systems;
Hands-on experience designing, implementing, and maintaining MLOps workflows, including CI/CD pipelines, monitoring, and production optimization;
Strong background in cloud computing with AWS or GCP, infrastructure as code with Terraform, containerization, and orchestration with Kubernetes;
Solid understanding of test-driven development, systems thinking, and CI/CD automation;
Experience deploying and managing Prometheus, Grafana, and OpenTelemetry for reliability and performance in production ML systems;
Expertise in scaling and optimizing distributed systems for large-scale, multi-node computations.