
AI/ML Engineer
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Remote - Global"), this listing's salary midpoint is about 93% lower. The offer sits below the benchmark range (€2,367–€14,758). The listed pay band (€422–€693) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 351 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| All roles in Remote - Global | €2,367/per month | €6,692/per month | €14,758/per month |
| Pay in our data — not quoted in ad (Senior) | €422/per month | €558/per month | €693/per month |
AI/ML Engineer Are you interested in quantum computing and quantum algorithms? Would you like to be part of a team unlocking the quantum advantage? Do you want to change the world? About this position QMill is developing new quantum algorithms and software solutions that could solve specific problems better than any existing classical solution. The problems can relate to optimization, simulation and machine learning, for example. Our first product, QMill Circuit Compression, was launched in November. QMill is well networked nationally and internationally and actively cooperates with the key players in the field. Get to know us further by visiting qmill.com. We are seeking an experienced AI/ML Engineer to lead the development of AI-powered agent systems and assistant tools that support quantum developers in their daily work — from code generation and circuit debugging to algorithm suggestion and research summarization.You’ll build AI systems that integrate with our internal workflows, collaborate with quantum engineers to understand pain points, and help define and deliver commercial services that enhance the productivity of quantum teams worldwide. This is a hybrid R&D + product engineering role, with high visibility and direct user impact.While a background in quantum computing is not mandatory, we seek individuals who possess a genuine interest in the potential of quantum computing and are eager to learn more about this groundbreaking field.What will you doDesign and build AI systems, assistants, and agents to support quantum software developers and researchers using LLM APIs or open-source models.Develop prompt-based tools, retrieval-augmented generation (RAG) systems, and multi-agent LLM workflows.Collaborate with quantum scientists and SW development team to productize AI models and agents in QMill core products and internal development tools and environmentsEnsure performance, reliability, and reproducibility of AI models and agents in sensitive environments.Productize and document AI model and agent features for wide adoption of internal and external usersIntegrate and deploy AI models via containerized environments and DevOps pipelines.Monitor, evaluate, and continuously improve model accuracy, latency, and robustness.We are looking forMinimum of 5 years of experience in AI/ML engineering or NLP/LLM systems development.Proficiency in Python and experience with modern ML workflows and librariesHands-on experience developing LLM-powered tools, AI agents or agentic frameworks.Understanding of how to build prompt pipelines, RAG systems, and optionally multi-agent workflows.Experience with backend integration, APIs, cloud deployments, and secure model inference.Understanding of ML ops best practices (e.g., model versioning, reproducibility, experiment tracking).Strong collaboration skills with engineering and product teams.Eagerness to work on real-world tooling supporting technical users.Understanding of quantum computing and quantum algorithms as well as familiarity with quantum computing frameworks, hybrid AI /quantum systems and DevOps tools is a plusMaster level degree in computer science, physics or mathematics. Ph.D. is a plusWhat you need to succeedGood at communicating and collaborating with peopleFluent in written and spoken EnglishProactive and creativeEfficient and productiveInterest and experience in AI-assisted toolsCuriosity and passion to explore the potential of quantum computingWhat we are offeringVisionary work in quantum algorithms and software. We offer positions at the cutting edge of technology, science and engineering of quantum algorithms. Our research agenda is dedicated to finding quantum advantage algorithms that can be used to solve specific problems or even systemic and technological challenges in society and business, so your work will be groundbreaking with a real, positive impact.Great career opportunities, and superb colleagues. Our personnel are highly educated research-oriented professionals. Collaborating in a multi-disciplinary team with top talent is a source of learning, inspiration, and fun. As we progress towards quantum advantage, there will be new roles and responsibilities to grow into.Support for your well-being. Without our personnel we cannot succeed, so we take good care of them. We aim to nurture great team spirit and leadership and enable a good work-life balance.Apply now and join our journey into the realm of quantum algorithms!Please send your CV and application with your salary request as soon as possible. We will process applications as they come in and fill in the position as soon as we find the right candidate.Interested and want to hear more?For further information, please contact Jouni Peltonen: info@qmill.comWe look forward to hearing from you!QMill – The first to unlock quantum advantage
Job Details
Responsibilities
- Design and build AI systems, assistants, and agents to support quantum software developers and researchers using LLM APIs or open-source models.
- Develop prompt-based tools, retrieval-augmented generation (RAG) systems, and multi-agent LLM workflows.
- Collaborate with quantum scientists and SW development team to productize AI models and agents in QMill core products and internal development tools and environments
- Ensure performance, reliability, and reproducibility of AI models and agents in sensitive environments.
- Productize and document AI model and agent features for wide adoption of internal and external users
- Integrate and deploy AI models via containerized environments and DevOps pipelines.
- Monitor, evaluate, and continuously improve model accuracy, latency, and robustness.
Skills & Technologies
Education Level
Masters
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