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AI/ML Engineer

AI/ML Engineer

Cognite

3 - 8 years

8 - 11 Lacs

bengaluru

Posted:Just now| Platform:

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Skills Required

deep learning version control orchestration pharma manager technology open source microsoft digital transformation python

Work Mode

Work from Office

Job Type

Full Time

Job Description

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

End-to-End Prototyping Build cross-stack prototypes using ATLAS AI, CDF, and open-source AI frameworks to solve real customer challenges.
Agent Workflow Design Design and implement multi-agent workflows that combine LLMs, tool use, and reasoning over industrial data.
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

3+ 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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AI/ML Engineer