Nebius Academy is a global AI education platform dedicated to empowering individuals and organizations to master AI and cloud technologies. We combine deep technical expertise with a vision for AI-powered education, supporting both individuals aiming to upskill for new career paths and companies pursuing innovation at scale.

We are looking for a technically strong and business-oriented AI expert to support the strategic development of our AI for Business programs. This is a technical and strategic advisory position focused on reviewing content, ensuring technical accuracy, and aligning our programs with how AI actually works and delivers measurable business results. You will act as a bridge between fast-evolving AI technologies and real-world business application.

What you will do:

Your role is to ensure that our AI programs are not superficial or tool-hyped, but grounded in how modern AI systems actually function and how they create value. That includes:

Review modules and frameworks for technical robustness.
Validate explanations of LLMs, agents, automation, and AI workflows.
Identify outdated practices and recommend updated approaches.
Advise on how emerging AI capabilities should reshape business use cases.
Provide feedback on implementation examples and ROI logic.
Help translate AI mechanisms into clear business impact narratives.

What we can offer you:

Pay Rate: $80/hr. - $100/hr. (gross).
Remote, hourly collaboration.
Free in-house training on educational best practices.
Opportunities to build your profile as a recognized public expert in AI strategy.
Cross-cultural work environment and extensive networking opportunities with passionate, mission-driven teammates.

We're excited to get to know you and work together!

Brand:
Nebius Academy
Requirements

Technical expertise:

1. Strong understanding of how modern AI systems work under the hood, including:

Large Language Models (LLMs) and transformer architectures
Context windows, tokenization, inference limitations
Retrieval-Augmented Generation (RAG)
Embeddings and vector search
API-based integrations
Agents and orchestration patterns
Model evaluation and output validation

2. Familiarity with leading AI ecosystems (OpenAI, Anthropic, Google, open-weight models) and their comparative strengths and limitations.

3. Ability to distinguish between:

Core model capabilities
Product wrappers and SaaS layers
Marketing hype vs actual technical progress

4. Strong awareness of current AI updates and releases, with the ability to assess their practical significance.

Business application experience:

1. Experience applying AI in real business environments (product, operations, marketing, analytics, automation, or consulting).

2. Understanding of:

AI adoption and implementation strategy
Workflow redesign (automation vs augmentation)
ROI estimation and value creation
Operational efficiency gains
Governance and responsible AI usage

3. Ability to connect technical AI decisions with measurable business outcomes.

What makes an ideal candidate:

Thinks in systems, not just tools.
Understands both AI mechanics and business implications.
Follows AI developments closely and evaluates them critically.
Comfortable challenging assumptions and identifying weak logic.
Not vendor-biased — compares models objectively.
Prioritizes depth and realism over hype.

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