At a Glance
- Tasks: Design and implement strategies for LLM training datasets and collaborate on innovative ML projects.
- Company: Fast-growing deep-tech company leading in quantum software and AI.
- Benefits: Signing bonus, relocation package, flexible hours, and equal pay.
- Why this job: Join a multicultural team at the forefront of AI and quantum computing.
- Qualifications: Master's/Ph.D. in relevant fields and 4+ years in data science or machine learning.
- Other info: Opportunity for career growth in a dynamic, international environment.
The predicted salary is between 48000 - 84000 Β£ per year.
Overview
At RemoteStar, we\βre currently hiring for one of our client based in Spain.
9-month fixed-term contract | Hybrid (3 days/week onsite) | Location: Barcelona or Madrid
About client:
Well-funded and fast-growing deep-tech company founded in 2019. We are the biggest Quantum Software company in the EU. They are also one of the 100 most promising companies in AI in the world (according to CB Insights, 2023) with 150+ employees and growing, fully multicultural and international. They provide hyper-efficient software to companies seeking to gain an edge with quantum computing and artificial intelligence. Their main products, Singularity and CompactifAI, address critical needs across various industries.
Required Qualifications
- Master\βs, or Ph.D. in Computer Science, AI, Data Science, Physics, Math, or a related field. Or equivalent industry experience.
- 4+ years of experience in data science, machine learning, or related roles, with demonstrated experience with NLP or LLMs.
- In-depth knowledge of large foundational model architectures (language and multimodal models) and their lifecycle: training, fine-tuning, alignment, and evaluation.
- Proficient in Python and data tooling ecosystems (Pandas, NumPy, Hugging Face Datasets & Transformers libraries).
- Hands-on experience with text data collection from diverse sources: web scraping, APIs, proprietary corpora, etc.
- Strong understanding of data quality metrics including bias detection, toxicity, and readability.
- Experience working in large shared distributed computing environments, familiarity with relevant tools for hardware optimization (vLLM, TensorRT, NeMo, etc.).
- Experience with version control (git), unit testing, and other fundamental aspects of software development.
- Effective communication and interpersonal abilities.
Preferred Qualifications
- Experience building or contributing to datasets used in LLM pretraining or supervised fine-tuning.
- Experience building foundational LLMs from the ground up
- Familiarity with alignment techniques (e.g., reinforcement learning, preference modeling, reward modeling).
- Exposure to multilingual and low-resource language datasets.
- Contributions to open-source datasets, tools, or publications in dataset-centric research.
- Knowledge of ethical AI, data governance, privacy laws (e.g., GDPR), and responsible data use.
- Familiarity with the software development lifecycle and agile methodologies
As a Senior LLM Engineer, you will
- Design and implement strategies for creating, sourcing, and augmenting datasets tailored for LLM training and fine-tuning.
- Develop scalable pipelines to collect, clean, filter, annotate, and validate large volumes of text data, ensuring quality, ethical compliance, etc.
- Collaborate with ML engineers, researchers, and software engineers to achieve ambitious goals in the preparation of LLMs and complementary work (preparing datasets, model evaluation, model serving, etc.).
- Develop and integrate new routines for modifying and enhancing LLMs, and extending their functionality.
- Make effective use of distributed compute resources and clusters (GPUs), identify opportunities for further optimization.
- End-to-end preparation of compressed and specialized LLMs for use in production.
- Keep up to date with research trends in LLM foundation models, dataset curation, LLM pretraining data, and benchmarking.
- Contribute to building documentation, development standards, and a healthy shared code base.
- Mentor other engineers and provide knowledge sharing of cutting-edge techniques.
We offer
- Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.
- Relocation package (if applicable).
- Up to 9-month contract, ending on 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.
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Senior Machine Learning Engineer (Spain) employer: RemoteStar
Contact Detail:
RemoteStar Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Senior Machine Learning Engineer (Spain)
β¨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We canβt stress enough how important it is to build relationships; sometimes, itβs not just what you know, but who you know!
β¨Tip Number 2
Prepare for those interviews! Research the company and its products, especially their work in quantum computing and AI. We recommend practising common interview questions and even some technical challenges related to machine learning to show off your skills.
β¨Tip Number 3
Showcase your projects! Whether itβs through a portfolio or GitHub, let your work speak for itself. We love seeing hands-on experience, especially with NLP and LLMs, so make sure to highlight any relevant projects you've worked on.
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets seen. Plus, weβre always looking for passionate individuals who want to be part of a fast-growing team in a multicultural environment. Donβt miss out!
We think you need these skills to ace Senior Machine Learning Engineer (Spain)
Some tips for your application π«‘
Tailor Your CV: Make sure your CV is tailored to highlight your experience in machine learning and data science. Use keywords from the job description, like NLP, LLMs, and Python, to show weβre on the same page.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and quantum computing, and explain how your background makes you a perfect fit for our clientβs needs. Keep it engaging and personal!
Showcase Relevant Projects: If you've worked on projects related to LLMs or dataset curation, make sure to mention them. We want to see your hands-on experience, so include links or descriptions that demonstrate your skills.
Apply Through Our Website: Donβt forget to apply through our website! Itβs the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we love seeing candidates who follow the process!
How to prepare for a job interview at RemoteStar
β¨Know Your Stuff
Make sure you brush up on your knowledge of large foundational model architectures and their lifecycle. Be ready to discuss your hands-on experience with NLP or LLMs, as well as any projects you've worked on that involved data collection and cleaning.
β¨Showcase Your Skills
Prepare to demonstrate your proficiency in Python and relevant data tooling ecosystems. Bring examples of how you've used libraries like Pandas and NumPy in your previous roles, and be ready to talk about your experience with version control and unit testing.
β¨Communicate Effectively
Since effective communication is key, practice explaining complex concepts in a simple way. Think about how you can convey your ideas clearly, especially when discussing technical topics related to machine learning and AI.
β¨Stay Current
Keep yourself updated on the latest research trends in LLM foundation models and dataset curation. Being able to discuss recent advancements or challenges in the field will show your passion and commitment to staying at the forefront of technology.