Junior Machine Learning Engineer
Multiverse Computing3 days ago
Barcelona, SpainEntry Level
Responsibilities
- Build end-to-end data and model pipelines, including dataset creation, sourcing, augmentation, validation, training, fine-tuning, evaluation, and model delivery.
- Design evaluation frameworks with statistical testing, reliability checks, and continuous evaluation for task competence and alignment.
- Scale training and inference using distributed compute while optimizing throughput and latency.
- Improve model capabilities and safety through supervised fine-tuning and reinforcement learning methods.
- Apply model compression and specialization techniques to meet performance and footprint targets.
- Collaborate with research and engineering teams and contribute reproducible, production-ready code to the shared codebase.
Requirements
- Bachelor’s degree in machine learning, computer science, mathematics, physics, or a related field.
- Up to two years of hands-on experience.
- Strong programming skills in Python and the modern machine learning stack, with basic software practices including Git, unit tests, and CI.
- Solid understanding of language modeling, including training, evaluation, model architecture, and data.
- Experience using GPU resources and familiarity with containerized workflows such as Docker and job schedulers or cloud orchestration.
- Ability to read research papers, prototype ideas quickly, and turn them into reproducible, production-ready code.
- Familiarity with AI or agentic workflows and task automation.
- Preferred: PhD or equivalent industry experience in machine learning, data science, or related roles, with demonstrated NLP or LLM experience.
- Preferred: experience building foundational LLMs, LLM evaluation harnesses, distributed training systems, model compression methods, or post-training reinforcement learning systems.
Benefits
- Indefinite contract and equal pay guarantee.
- Variable performance bonus and signing bonus.
- Work visa sponsorship and relocation package where applicable.
- Private health insurance, flexible remuneration for hospitality and public transportation, and an educational budget subject to internal policy.
- Hybrid work opportunity and flexible working hours.
- Language classes and discounted lunch options.
- Career plan, learning and teaching opportunities, and an inclusive company culture.
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