Multiverse Computing · AI infrastructure
Senior Machine Learning Engineer (LLM)
- Zaragoza (Hybrid)
AI roleMachine LearningTrains models
Still open on Multiverse Computing's site · checked 2 hours ago
- Level
- Senior
- Experience
- 5+ years
- Education
- Bachelor's degree
- Posted
- Visa & relocation
- Multiverse Computing offers visa sponsorship for this job
- Multiverse Computing offers relocation support for this job
See all jobs with visa or relocation supportIn the job ad:
“We offer work visa sponsorship (If applicable).”
“Relocation package (if applicable).”
What you'll do
As written by Multiverse Computing · Read the original
As a Machine Learning Engineer, you will
Design and develop new techniques to compress Large Language Models based on quantum-inspired technologies to solve challenging use cases in various domains.
Conduct rigorous evaluations and benchmarks of model performance, identifying areas for improvement, and fine-tuning and optimising LLMs for enhanced accuracy, robustness, and efficiency.
Build LLM based applications such as RAG and AI agents.
Use your expertise to assess the strengths and weaknesses of models, propose enhancements, and develop novel solutions to improve performance and efficiency.
Act as a domain expert in the field of LLMs, understanding domain-specific problems and identifying opportunities for quantum AI-driven innovation.
Design, train and deliver custom deep learning models for our clients
Work in diverse areas beyond LLM, e.g., computer vision.
Maintain comprehensive documentation of LLM development processes, experiments, and results.
Share your knowledge and expertise with the team to foster a culture of continuous learning, guiding junior members of the team in their technical growth and helping them develop their skills in LLM development.
Participate in code reviews and provide constructive feedback to team members.
Stay up to date with the latest advancements and emerging trends in LLMs and recommend new tools and technologies as appropriate.
Required minimum Qualifications:
Bachelor's, Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.
5+ years of hands-on experience with designing, training or fine-tuning deep learning models, preferably working with transformer or computer vision models.
5+ year of hands-on experience using transformer models, with excellent command of libraries such as HuggingFace Transformers, Accelerate, Datasets, etc."
Solid mathematical foundations and theoretical understanding of deep learning algorithms and neural networks, both training and inference.
Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.
Strong understanding with the fundamentals of GPU architectures and LLM hardware/ software infrastructures.
Excellent programming skills in Python and experience with relevant libraries (PyTorch, HuggingFace, etc.).
Experience with cloud platforms (ideally AWS), containerization technologies (Docker) and with deploying AI solutions in a cloud environment
Excellent written and verbal communication skills, with the ability to work collaboratively in a fast-paced team environment and communicate complex ideas effectively.
Previous research publications in deep learning or any tech field is a plus
Fluent in English
Requirements
Preferred Qualifications
Experience running large-scale workloads in high-performance computing (HPC) clusters.
Experience in handling large datasets and ensuring data quality.
Experience with inference and deployment environments (TensorRT, vLLM, etc.).
Experience in accuracy evaluation of LLMs (OpenLLM Leaderboard).
Experience building and evaluating RAG systems.
Experience in building non-LLM deep learning applications, e.g., computer vision, audio or signal processing.
Familiarity with AI ethics and responsible AI practices.
Experience in DevOps/MLOps practices in deep learning product development.
Skills
Stack
- Python
- PyTorch
- Hugging Face Transformers
- Transformers
- vLLM
- AWS
- Docker
Working languages
English
Salary & benefits
Perks and 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.
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.
Company
Last checked . The details above were extracted automatically; the employer's original posting is the authority.