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For Companies At a Glance
- Tasks: Experiment with cutting-edge language models and optimise AI performance.
- Company: Fastino, a pioneering tech company backed by top investors.
- Benefits: Remote work, competitive salary, and opportunities for travel to Silicon Valley.
- Why this job: Join a team of experts and shape the future of AI technology.
- Qualifications: Experience in AI product development; advanced degrees and research experience are a plus.
- Other info: Dynamic environment with significant career growth and collaboration opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Join us at Fastino as we build the next generation of LLMs. Our team, boasting alumni from Google Research, Apple, Stanford, and Cambridge is on a mission to develop specialized, efficient AI.
Fastino's GLiNER family of open source models has been downloaded more than 5 million times and is used by companies such as NVIDIA, Meta, and Airbnb. Fastino has raised $25M through our seed round and is backed by leading investors including Microsoft, Khosla Ventures, Insight Partners, Github CEO Thomas Dohmke, Docker CEO Scott Johnston, and others.
What You’ll Work On
- Experiment with novel language model architectures, helping drive and execute Fastino's research roadmap.
- Optimize Fastino’s multimodal models to improve response quality, instruction adherence, and overall performance metrics.
- Architect data processing pipelines, implementing filtering, balancing, and captioning systems to ensure training data quality across diverse content categories.
- Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards.
- Build robust and real-world motivated evaluations.
- Partner with Fastino engineering team to ship model updates directly to customers.
- Establish best practices for code health and documentation on the team, to facilitate collaboration and reliable development.
What We’re Looking For
- Required: Great velocity for building and shipping agents / AI products.
- Optional: Advanced degree (Master's or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related technical discipline with concentrated study in deep learning and computer vision methodologies.
- Optional: Demonstrated ability to do independent research in Academic or Industry settings.
- Optional: Substantial industry experience in large-scale deep learning model training, with demonstrated expertise in at least one of Large Language Models, Vision-Language Models, Diffusion Models, or comparable generative AI architectures.
- Optional: Comprehensive technical proficiency and practical experience with leading deep learning frameworks, including advanced competency in one of PyTorch, JAX, TensorFlow, or equivalent platforms for model development and optimization.
Research Engineer- Large Language Models employer: fastino.ai
Contact Detail:
fastino.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer- Large Language Models
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those connected to Fastino. LinkedIn is your best mate here; drop them a message and express your interest in their work. You never know who might give you a nudge in the right direction!
✨Tip Number 2
Show off your skills! If you've got projects or research that align with what Fastino is doing, make sure to highlight them in conversations. Bring your portfolio to life by discussing how your experience can contribute to their mission of developing efficient AI.
✨Tip Number 3
Prepare for the interview like it’s a big game! Research Fastino’s GLiNER models and be ready to discuss how you can optimise their multimodal models. Brush up on reinforcement learning techniques too; they’ll want to see you’re on top of your game!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Fastino team. Let’s get you that dream job!
We think you need these skills to ace Research Engineer- Large Language Models
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Research Engineer role. Highlight your experience with large language models and any relevant projects you've worked on. We want to see how your skills align with what we're doing at Fastino!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and why you’re excited about working with us at Fastino. Let us know how your background makes you a great fit for our team.
Showcase Your Projects: If you've worked on any interesting projects related to AI or deep learning, make sure to mention them! We love seeing practical applications of your skills, so don’t hold back on sharing your achievements.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at fastino.ai
✨Know Your Models
Make sure you brush up on the latest advancements in large language models and related architectures. Be ready to discuss your experience with specific frameworks like PyTorch or TensorFlow, as well as any projects you've worked on that relate to AI products.
✨Showcase Your Research Skills
If you have experience in independent research, prepare to share insights from your work. Highlight any novel approaches you've taken or challenges you've overcome, especially in deep learning or multimodal models. This will demonstrate your ability to contribute to Fastino's innovative environment.
✨Understand the Company’s Mission
Familiarise yourself with Fastino's GLiNER models and their impact in the industry. Being able to articulate how your skills align with their mission to develop efficient AI will show that you're genuinely interested in the role and the company.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Brush up on reinforcement learning techniques and be ready to explain how you would implement them in practice. Practising coding problems or system design questions can also help you feel more confident.
