Our client maps cities across the world, providing businesses with high-quality visuals and 3D models to enhance insights and daily decision-making.
In this role, you’ll collaborate closely with data scientists and ML engineers to ensure seamless model integration into reliable, production-grade systems.
You’ll focus on automating workflows, enhancing observability, and optimizing system performance—not just DevOps for AI, but true software engineering for machine learning at scale.
Up to 32,000 PLN per month
100% Remote in Poland
Full-time
B2B Contract
responsibilities :
Spearheading the design, implementation, and scaling of sophisticated systems that support advanced machine learning operations
Lead initiatives to streamline workflows for data scientists and ML engineers, fostering seamless collaboration and enhanced productivity
Overseeing the development and maintenance of LLM and generative AI systems, ensuring scalability, security, and operational efficiency
Guide the teams in deploying monitoring and observability solutions to maintain high availability and reliability in production ML environments
Manage complex, interdependent projects, aligning business goals with technical excellence
Coach senior engineers and play a pivotal role in shaping MLOps culture, processes, and long-term strategic vision.
requirements-expected :
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.
8+ years of hands-on experience across Machine Learning, MLOps, DevOps, and software engineering, with a track record of leading large-scale ML operations
Deep understanding of end-to-end MLOps workflows, including lifecycle management, monitoring, and optimization of LLMs and generative AI models
Familiarity with observability tools (OpenTelemetry, Prometheus, Grafana), container orchestration (Kubernetes), and cloud infrastructure management (AWS, Terraform) is a strong advantage is a plus
Experience guiding senior engineers and shaping organizational culture, best practices, and engineering processes
