Sigma Nova

Sigma Nova builds large-scale AI foundations to accelerate scientific breakthroughs. It develops foundation models and Gen AI capabilities through partnerships that unlock diverse datasets from institutions, corporations, and academics. Key technologies include foundation models, data collaboration platforms, and interdisciplinary teams. The company operates as a Gen AI lab serving research institutions and industry partners. This approach aims to scale scientific discovery across sectors by enabling collaborative AI-driven research.

Artificial Intelligencesigmanova.ai

Sigma Nova

Artificial Intelligencesigmanova.ai

HQParis, FR

Team Size8

Open Jobs5

Total Funding-

Latest FundraiseUnknown

Join the Team

AI Research Program Manager

HybridRue de Mogador, 75009 Paris, France, FR

Hybrid • Rue de Mogador, 75009 Paris, France, FR

Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.

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AI Researcher

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Internship • Rotterdam, NL

Product Designer

ContractBelgrade, RS

Contract • Belgrade, RS

Software Engineer

InternshipJerusalem

Internship • Jerusalem

Data Scientist

InternshipSan Francisco, US

Internship • San Francisco, US

Technical Writer

Part-timeNiš, RS

Part-time • Niš, RS

Orchestrate the production and delivery of scientific AI components across our research squads, creating the execution framework that transforms our scientific ambitions into concrete, interoperable, and reusable deliverables.

Squad orchestration and coordination

Work with the CEO and Strategy team to translate scientific use cases into squadized execution plans (objectives, tempo, milestones, trade-offs)
Coordinate squads throughout the AI component development cycle: synchronization across domains (neuroimaging, data infra, ML), tempo management, feedback facilitation
Actively manage inter-squad dependencies, risks, and decisions, maintaining the balance between scientific exploration and robust execution

Delivery process structuring

Establish and maintain a common delivery framework: documentation, demo formats, tracking tools, definition of “delivered capability”
Structure a cross-functional delivery process including cadence, validation milestones, use case prioritization
Establish and stabilize the “Use Case → Squad → Capability → Demo” cycle with regular feedback and clear decisions

Tracking and management

Ensure incremental delivery of foundational components (pipelines, modules, frameworks) with precise maturity tracking
Facilitate execution rituals adapted to R&D (lightweight sprint cycles, progress reviews, synchronization)
Identify and resolve operational blockers, propose process adjustments### Core experience and skills
6-12 years of experience managing complex projects/programs, ideally in innovation, AI, or deeptech

Methodological skills

Proficiency or strong appetite for agile methods adapted to R&D (scientific Kanban, component-oriented roadmap, use-case scoping)
Comfort with modern collaboration tools (Notion, GitHub, Miro, spreadsheets, roadmap visualization)
Ability to create structure in ambiguity without constraining scientific exploration

Personal qualities

Strong autonomy and initiative within a structured framework
Excellent interpersonal and diplomatic skills (influence without hierarchical authority)
Comfort working with senior scientific profiles (PhDs, research leads)
Intellectual curiosity for science and technology (no need to be an engineer, but genuine interest required)

Nice to have

Experience in an AI lab, deeptech startup, or organization applying research to technology
Familiarity with ML issues, neuroscience, or scientific data (EEG, MEG, etc.)- Prescreen with (Head of People)
Hiring Manager screen (CEO)
Onsite interview