Senior Machine Learning Engineer (LLM)
Multiverse Computing2 days ago
Zaragoza, SpainSenior
Responsibilities
- Design and develop quantum-inspired techniques to compress large language models for real-world use cases.
- Conduct model evaluations and benchmarks, fine-tune and optimize LLMs, and improve their accuracy, robustness, and efficiency.
- Build LLM-based applications such as retrieval-augmented generation systems and AI agents.
- Design, train, and deliver custom deep learning models for clients, including applications beyond LLMs such as computer vision.
- Assess model strengths and weaknesses, propose improvements, and identify opportunities for quantum AI-driven innovation.
- Maintain documentation of LLM development processes, experiments, and results.
- Collaborate with cross-functional teams, participate in code reviews, and provide technical feedback.
- Share expertise and guide junior team members in their technical growth.
- Stay current with LLM advancements and recommend appropriate tools and technologies.
Requirements
- Bachelor's, Master's, or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or a related field.
- At least 5 years of hands-on experience designing, training, or fine-tuning deep learning models, preferably transformer or computer vision models.
- At least 5 years of hands-on experience using transformer models and libraries such as HuggingFace Transformers, Accelerate, and Datasets.
- Strong mathematical foundations and theoretical understanding of deep learning algorithms and neural networks, including training and inference.
- Strong problem-solving, debugging, performance analysis, test design, and documentation skills.
- Strong understanding of GPU architectures and LLM hardware and software infrastructure.
- Excellent Python programming skills and experience with relevant libraries such as PyTorch and HuggingFace.
- Experience with cloud platforms, ideally AWS, containerization technologies such as Docker, and deploying AI solutions in cloud environments.
- Excellent written and verbal communication skills and the ability to collaborate and explain complex ideas effectively.
- Fluent English.
- Previous research publications in deep learning or another technology field are a plus.
- Preferred experience includes HPC clusters, large datasets and data quality, TensorRT, vLLM, LLM accuracy evaluation, OpenLLM Leaderboard, RAG systems, non-LLM deep learning applications, AI ethics, responsible AI, and DevOps/MLOps practices.
Benefits
- Indefinite contract.
- Equal pay guarantee, variable performance bonus, and signing bonus.
- Work visa sponsorship if applicable.
- Relocation package if applicable.
- Private health insurance.
- Eligibility for an educational budget according to internal policy.
- Hybrid work opportunity and flexible working hours.
- Language classes and discounted lunch options.
- Career plan and opportunities to learn and teach.
- Inclusive, progressive company culture.
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