Machine Learning Engineer (Product) (Fixed-term contract)

• Build data and model pipelines end-to-end: create, source, augment, and validate datasets; stand up training/fine-tuning/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 systems-level speedups.

• Improve models post-training: apply SFT and preference-based or reinforcement learning methods to enhance helpfulness, safety, and reasoning.

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

• Collaborate across research and engineering: partner with ML engineers, researchers, and software engineers on data curation, evaluation design, training runs, model serving, and observability.

• Contribute to our shared codebase: write clean, well-tested Python; document decisions and artifacts; uphold engineering standards.

• This role requires a Bachelor's degree in Computer Science, Math, Physics, Physics, Data Science, Operations Research, or related field.

• Strong programming skills in Python and the modern ML stack (e.g., PyTorch), plus fluency with data tooling (NumPy/Pandas) and basic software practices (git, unit tests, CI).

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

• Comfort working with datasets at scale: collection, cleaning, filtering, labelling/annotation strategies, and quality controls.

• 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, production-ready code.

• Clear, pragmatic communication and a collaborative mindset.

Preferred Qualifications

• PhD in Computer Science, Math, Physics, Data Science, Operations Research, 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 task-grounded evals for LLMs, implementing or extending evaluation harnesses, and generating synthetic data for both evaluation and training; deep understanding of LLM quirks and their ties to architecture and training dynamics.

• Distributed Training: Hands-on experience debugging multi-node 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 trade-offs and to integrate results into production.

• Post-Training: Theoretical and practical familiarity with post-training and alignment techniques; experience with SFT and preference/RL-based methods (e.g., DPO/GRPO, RLHF).

• Competitive annual salary starting from €45,000, based on experience and qualifications.

• Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.

• Relocation package (if applicable).

• Fixed-term contract ending in June 2026.

• Hybrid role and flexible working hours.

• Be part of a fast-scaling Series B company at the forefront of deep tech.

• Equal pay guaranteed.

• International exposure in a multicultural, cutting-edge environment.

Multiverse is a well-funded and fast-growing deep-tech company founded in 2019. We are one of the few companies working with Quantum Computing and the biggest Quantum Software company in the EU.
We provide hyper-efficient software to companies wanting to gain an edge with quantum computing and artificial intelligence. Our product, Singularity, is a software platform that contains quantum and quantum-inspired algorithms developed and patented through proof-of-concept trials we have been performing for industrial and service clients. We work in finance, energy, manufacturing, cybersecurity and many more industries.

Digital methods usually fail at efficiently tackling these problems. Quantum computing, however, provides us with a powerful toolbox to tackle these complex problems, such as outstanding optimization methods, software for quantum machine learning, and quantum enhanced Monte Carlo algorithms.

Multiverse Computing applies these cutting edge methods to provide software which is customized to your needs, giving companies a chance to derive value from the second quantum revolution.