You bring a strong combination of machine learning infrastructure expertise, software engineering excellence, and a passion for building reliable production systems.
You have a Master's degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, or a related field, along with demonstrated experience delivering machine learning systems into production environments at scale.
- 4+ years of experience in MLOps, ML platform engineering, or ML infrastructure engineering.
- Deep expertise across the machine learning lifecycle, including training, evaluation, deployment, monitoring, and retraining.
- Strong experience implementing CI/CD pipelines, automated testing, model packaging, and release management for ML systems.
- Hands-on proficiency with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP, including infrastructure-as-code practices.
- Experience building scalable model-serving solutions supporting both batch and real-time inference workloads.
- Strong knowledge of observability, monitoring, data drift detection, model validation, and operational excellence.
- Proficiency in Python and strong software engineering fundamentals, including testing, code quality, and version control.
- Experience with workflow orchestration and MLOps platforms such as MLflow, Kubeflow, Airflow, DVC, or comparable technologies.
- Practical experience supporting large-scale data processing environments, distributed computing, streaming architectures, or Spark-based systems.
- Familiarity with LLMOps practices, retrieval infrastructure, vector databases, and operationalization of AI-powered systems.
- The ability to make informed architectural decisions, lead technical initiatives, and collaborate effectively across multidisciplinary teams.
- Excellent communication, mentoring, and stakeholder engagement skills.
Exposure to geospatial platforms, spatial data infrastructure, edge AI, TinyML, LiDAR, drone data processing, Go, Java, or C++ is valuable in helping accelerate impact within HERE’s innovation ecosystem.
What we offer
HERE offers an opportunity to work in a cutting-edge technology environment with challenging problems to solve! You can make a direct impact on delivery of company´s strategic goals and the freedom to decide how to perform your work. We will support you in delivering your day-to-day tasks and achieving your personal goals and developing your skills. Personal development is highly encouraged at HERE. You can take different courses and training at our online Learning Campus and join cross-functional team projects within our Talent Platform.
HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.