Machine Learning Engineer

RemoteStar; España; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Signing bonus

Relocation package

Private health insurance

Educational budget

Language classes and discounted lunch

High paced environment

Job summary

RemoteStar is seeking an experienced Machine Learning Engineer with a strong background in Large Language Models to lead design, implementation, and improvement of language models. You will work across cross-functional teams to integrate models into products, exploring quantum-inspired approaches and cutting-edge AI research.

The role emphasizes building LLM-based applications, benchmarking performance, and collaborating in a fast-paced environment while contributing to the advancement of NLP

Qualifications

• Bachelor's/Master's/PhD in AI/CS/DS or related field.
• 5+ years designing or fine-tuning DL/transformer models.
• Experience with transformer libraries (HuggingFace, etc.).
• Strong math and theory in DL and neural networks.

Responsibilities

• Design and implement methods to optimize and compress LLMs.
• Benchmarks and evaluations to improve accuracy and efficiency.
• Build LLM-based apps such as RAG and AI agents.
• Collaborate with cross-functional teams and document experiments.
• Guide junior members and participate in code reviews.

Skills

Deep learning

Transformer models

Python programming

GPU architectures

Experimentation & debugging

Communication skills

Education

Bachelor/Master/PhD in AI/CS/DS

Tools

PyTorch

HuggingFace

Accelerate

Datasets

Docker

AWS

Job description

Work Mode: Hybrid (3 days from office, 2 day remote)

Job Overview

We are seeking a skilled and experienced Machine Learning Engineer with a strong background in Large Language Models to join our team. In this role you will have the opportunity to leverage cutting-edge quantum and AI technologies to lead the design, implementation, and improvement of our language models, as well as working closely with cross-functional teams to integrate these models into our products. You will have the opportunity to work on challenging projects, contribute to cutting-edge research, and shape the future of LLM and NLP technologies.

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

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.

Perks and Benefits

• Signing bonus.
• Relocation package (if applicable).
• Private health insurance.
• Eligibility for educational budget according to internal policy.
• Language classes and discounted lunch options
• Working in a high paced environment, working on cutting edge technologies.