We make quantum computing useful for industry

Define and execute the applied quantum research roadmap: identify high-impact use cases and validate quantum approaches against classical baselines

Design, implement, and benchmark quantum and hybrid algorithms with a focus on near-term hardware feasibility

Maintain deep fluency in the quantum hardware landscape: noise models, gate fidelities, connectivity constraints, and coherence times

Consolidate all research outputs into the platform's internal library, ensuring reproducibility and reusability

Write clean, well-documented research code for production integration

Publish peer-reviewed papers and file patents to build the company's IP portfolio

Lead and mentor a research team of up to 5

When relevant, contribute to client PoC engagements

PhD in quantum computing, quantum physics, or quantum chemistry

Deep knowledge of quantum algorithms, error mitigation, tensor network methods, and simulation techniques

Strong understanding of quantum hardware constraints and how they shape algorithm design

Proven publication track record in quantum computing

Strong Python skills; experience with quantum frameworks

Experience leading or mentoring a research team

Ability to translate research findings into product features, IP, and client value

Experience with quantum chemistry packages (PySCF, OpenFermion, or similar)

Patent filing experience

Prior work in an industry lab or applied research role

Familiarity with classical ML/optimization methods

Shape the Quantum Research Agenda: you define what we investigate and why

Research That Ships: every algorithm reaches real users through the platform

QPU credits across multiple hardware vendors

Dedicated engineering team translates your research into production

Build and mentor your own team of up to 5 researchers

Remote-first with full autonomy and equity participation

Design, develop, and maintain agentic AI systems built on LLM provider APIs (multi-agent pipelines, tool-calling workflows, orchestration logic)

Contribute to the architecture of complex, large-scale AI solutions

Integrate LLMs into product features ensuring reliability, scalability, and maintainability

Make architectural decisions within an engineering team (2–3 developers)

Track the fast-moving LLM/agentic ecosystem and propose migrations to better tools

Step into client ML projects as needed (forecasting, anomaly detection, classification)

3+ years of hands-on experience in AI/ML engineering

Strong Python skills with production-grade system experience

Deep understanding of the LLM stack: prompt engineering, function calling, RAG, context management

Practical experience with agentic system design and multi-agent workflows

Experience working with LLM provider APIs (Anthropic, OpenAI, or similar)

Solid classical ML skills

Ability to own solutions end-to-end: from architecture to deployment

Interest in quantum computing (Qiskit/PennyLane experience is a bonus)

Experience with quantum ML

Work at the intersection of two frontiers: LLM agents and quantum ML

Architectural influence from day one in a small, early-stage team

LLM budget and infrastructure: access to models and API credits

Learn quantum computing through practice alongside physicists and researchers

Remote-first with full autonomy and flexible hours

Equity participation and performance bonuses

Identify, qualify, and engage potential enterprise clients in target verticals (finance, energy, manufacturing, pharma, logistics)

Build relationships with high-profile companies and leading academic institutions

Navigate complex B2B sales cycles from outreach through contract signature

Develop and execute go-to-market strategies for EU, UK, and Switzerland

Collaborate with the technical team to scope PoC engagements

Represent Superpositions Studio at industry events and conferences

Provide market feedback to inform product development

3+ years of B2B sales or business development in deep tech, SaaS, or enterprise software

Experience or strong interest in quantum computing, AI/ML, or adjacent fields

Proven track record of closing enterprise deals and building strategic partnerships

Comfortable engaging in technical conversations with engineers and researchers

Self-motivated and comfortable in an early-stage environment

Excellent communication skills in English; additional European languages are a plus

Competitive base salary plus significant commission on signed contracts

Remote-first with full autonomy over your schedule

Equity participation as the company grows

Shape the commercial direction of an innovative quantum platform

Work alongside quantum computing and ML experts

No-hype culture: substance, honesty, and results over spin