AI/ML Engineer

2 days ago

Bengaluru, Karnataka, India Cognite Full time

About Cognite & ATLAS AI

Cognite is a global industrial AI software-as-a-service (SaaS) company supporting the full-scale digital transformation of heavy-asset industries around the world. Our core product, Cognite Data Fusion (CDF), is a leading industrial DataOps platform. Building on CDF, ATLAS AI is our innovative offering designed to deliver bold, customer-centric innovation powered by artificial intelligence.

The Role

As an 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 optimize 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 & 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 & Integration Evaluate and integrate new GenAI tools, open-source frameworks, and APIs into ATLAS AI workflows.
  • System Optimization Benchmark performance, tune retrieval and reasoning pipelines, and ensure scalability in real-world industrial deployments.
  • Collaboration & Co-Innovation Work with solution engineers and customer teams to align models and agent behaviors with business value and industrial constraints.

What We're Looking For

Must-Have Skills

  • 6+ years of experience in AI/ML engineering, with hands-on delivery of models.
  • Proficiency in working with foundation models (LLMs), including:
  • Prompt engineering, evaluation, and (when relevant) fine-tuning.
  • 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 labeling, 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 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 labeling industrial datasets, including annotation strategies and working with imperfect or sparse labels.

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