Principal ML Engineer

the team moving fast and safely. The Impact you bring to Cognite Key

Responsibilities Study, transform, and deploy data science prototypes into production environments, ensuring they are scalable, efficient, and maintainable. Architect and write high-quality, scalable, and testable production code (Python, Scala, C++, or Java). Build the robust APIs, distributed big data pipelines, and orchestration layers required to integrate AI into existing industrial master data systems. Navigate complex deployment environments. You will optimize inference bottlenecks, manage containerized deployments, and ensure our systems can handle massive volumes of unstructured industrial data reliably. Research and implement advanced ML algorithms (e.g., in NLP, Computer Vision) and extend existing ML libraries and frameworks. Run tests, perform statistical analysis, and monitor deployed models for performance, drift, and accuracy, implementing retraining strategies as needed. Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals. Provide technical mentorship to junior team members, guide code reviews, and help define technical standards for

the team. Required Skills and

Qualifications Bachelor’s or Master's degree in Computer Science, Data Science, or a related field (PhD is often preferred for higher-level roles). 10+ years of industry experience in machine learning and software development. Strong programming skills in Python, C++, or Java. Expertise in frameworks like PyTorch, TensorFlow, Keras, or Scikit-learn. Familiarity with MLOps best practices and cloud platforms such as AWS, Azure, or GCP. Solid understanding of data structures, algorithms, and software architecture. Preferred

Qualifications Deep expertise designing complex AI systems from the ground up, including fine-tuned multimodal models for dense diagrams (P&IDs, CAD), Agentic AI for multi-step reasoning, and advanced Graph RAG/Knowledge Graphs. Experience architecting modern lakehouses (e.g., Delta Lake, Apache Iceberg) to process and manage massive, complex datasets specific to manufacturing, supply chain, or OT (Operational Technology) environments. Proven ability to optimize large language models for maximum throughput and low latency, with experience deploying AI into highly secure, on-premises, or edge environments. What Sets Senior Roles Apart The ability to lead large, complex projects from design through deployment. Experience with high-scale machine learning environments, distributed computing, and optimizing model inference latency. Translating complex ML concepts into business insights for stakeholders. Learn more

about us Impact 2025 Cognite's Industrial AI: Moonshot We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi. Equal Opportunity Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

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