Cognite - Senior AI/ML Engineer

2 weeks ago


Bengaluru, India Cognite Full time

Description :As a Senior AI/ML Engineer in the ATLAS AI Co-Innovation team, you will help push the technical boundaries of what's possible with industrial GenAI. You'll design and optimise advanced AI models and agent architectures that interact with complex, real-world industrial data. You'll operate at the technical core of customer-facing coinnovation, working closely with solution engineers, product teams, and customer data to build smart, scalable AI components that power next-generation industrial workflows. This role demands strong AI/ML engineering skills, deep curiosity, and the ability to adapt cutting-edge research into usable, high-impact solutions.Responsibilities :- Model Development and Application : Design and apply foundation models to domain-specific tasks, focusing on prompt engineering, reasoning workflows, and tool use with attention to accuracy, robustness, and real-world applicability.- Agent Architecture Design : Develop modular, production-ready agent workflows integrated with CDF and ATLAS AI, leveraging tools, memory, reasoning chains, and APIs.- Tech Exploration and Integration : Evaluate and integrate new GenAI tools, open-source frameworks, and APIs into ATLAS AI workflows.- System Optimisation : Benchmark performance, tune retrieval and reasoning pipelines, and ensure scalability in real-world industrial deployments.- Collaboration and Co-Innovation : Work with solution engineers and customer teams to align models and agent behaviours with business value and industrial constraints.Requirements :- 5+ years of experience in AI/ML engineering, with hands-on delivery of models.- Proficiency in working with foundation models (LLMs), including :1. Prompt engineering, evaluation, and (when relevant) fine-tuning.2. RAG pipelines and integration with knowledge bases or vector databases.- Strong Python skills with experience using frameworks such as LangChain, Transformers, or similar.- Understanding of cloud-native development, model training workflows, and ML pipeline orchestration (e. g., data labelling, feature selection, model retraining).- Proven ability to write clean, maintainable, and scalable code, following engineering best practices for testing, version control, and review.- A maker mindset with a bias toward rapid iteration, showing rather than telling, and learning by doing.Bonus Skills :- Experience with Cognite Data Fusion (CDF). - Experience integrating AI workflows with time series, asset hierarchies, or knowledge graphs.- Deep learning or traditional ML background (e. g., model architecture selection, hyperparameter tuning, evaluation pipelines).- Understanding of industrial data types (e. g., time series, contextual events, industrial knowledge graphs).- Experience in labelling industrial datasets, including annotation strategies and working with imperfect or sparse labels. (ref:hirist.tech)



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