Junior Machine Learning Engineer

Multiverse is a well-funded fast-growing deep-tech company founded in 2019. We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.
With 180 employees and growing our team is fully multicultural and international. We deliver hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence.
Our flagship products CompactifAI and Singularity address critical needs across various industries:

CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks. It enables the compression of large AI systemssuch as language modelsto make them significantly more efficient and portable.

Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance energy manufacturing and beyond. It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware.

Youll be working alongside world-leading experts to develop solutions that tackle real-world challenges. Were looking for passionate individuals eager to grow in an ethics-driven environment that values sustainability and diversity.

Were committed to building a truly inclusive culturecome and join us.

As a Machine Learning Engineer you will

• In general: Build data and model pipelines endtoend: create source augment and validate datasets; stand up training/finetuning/evaluation flows; and ship models that meet product and customer requirements.

• Design rigorous evaluation frameworks to verify task competence and alignment; implement statistical testing reliability checks and continuous evaluation.

• Scale training and inference: make effective use of distributed compute optimize throughput/latency and identify opportunities for algorithmic or systemslevel speedups.

• Improve models posttraining: apply SFT and reinforcement learning methods to enhance model capabilities and safety.

• Optimize and specialize models: apply compression techniques to meet performance and footprint targets.

• Collaborate across research and engineering and contribute to our shared codebase; uphold engineering standards.

• This role requires a Bachelors degree in ML Computer Science Math Physics or related field.

• Upto 2 years of hands-on experience. Strong programming skills in Python and the modern ML stack and basic software practices (git unit tests CI).

• Solid grounding in language modelling concepts around training evaluation model architecture and data.

• Experience using GPU resources and familiarity with containerized workflows (e.g. Docker) and job schedulers or cloud orchestration.

• Ability to read research papers prototype ideas quickly and turn them into reproducible productionready code.

• Familiarity with AI / agentic workflows and task automation.

Preferred Qualifications

• PhD in ML Computer Science Math Physics Data Science or related field or equivalent industry experience in machine learning data science or related roles with demonstrated experience with NLP or LLMs.

• Experience building foundational LLMs from the ground up.

Preferred qualifications by focus area:

• Model Evaluation: track record building taskgrounded evals for LLMs implementing or extending evaluation harnesses; deep understanding of LLM capabilities and quirks and their ties to architecture and training dynamics.

• Distributed Training: Handson experience debugging multinode training profiling/optimizing throughput and memory and extending training frameworks like to new architectures or optimizers; comfort diagnosing flaky cluster issues.

• Model Compression: Strong mathematical background and experience with pruning quantization and NAS; ability to formulate and solve constrained optimization problems for accuracy/latency/footprint tradeoffs and to integrate results into production.

• PostTraining: Theoretical and practical familiarity with RL theory frameworks and monitoring.

Perks & Benefits

• Indefinite contract.

• Equal pay guaranteed.

• Variable performance bonus.

• Signing bonus.

• We offer work visa sponsorship (If applicable).

• Relocation package (if applicable).

• Private health insurance.

• Flexible remuneration: hospitality and public transportation.

• Eligibility for educational budget according to internal policy.

• Hybrid opportunity.

• Flexible working hours.

• Language classes and discounted lunch options

• Working in a high paced environment working on cutting edge technologies.

• Career plan. Opportunity to learn and teach.

• Progressive Company. Happy people culture
  

As an equal opportunity employer Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds including age citizenship ethnic and racial origins gender identities individuals with disabilities marital status religions and ideologies and sexual orientations to apply.