At a Glance
- Tasks: Train cutting-edge ML models to solve real-world enterprise problems.
- Company: Join Scale, a leader in AI data solutions for 8 years, driving innovation in AI applications.
- Benefits: Enjoy flexible work options, competitive pay, and the chance to work on groundbreaking projects.
- Why this job: Be at the forefront of AI technology, collaborating with top clients and shaping the future of AI.
- Qualifications: 1-3 years in ML model training, strong NLP skills, and a relevant degree.
- Other info: Opportunity to publish research and work with advanced AI technologies.
The predicted salary is between 48000 - 84000 £ per year.
AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative AI Platform (SGP). The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale.
As an ML Engineer, you’ll work with clients to train ML models to satisfy their business needs. Your work will range from training next-generation AI cybersecurity firewall LLMs to training foundation genomic models making predictions about life-saving drug proteins. Having a deep curiosity about the hardest questions about LLMs will also motivate various research opportunities on how to apply ML to the forefront of enterprise data. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!
You will:
- Train state of the art models, developed both internally and from the community, in production to solve problems for our enterprise customers.
- Work with product and research teams to identify opportunities for ongoing and upcoming services.
- Explore approaches that integrate human feedback and assisted evaluation into existing product lines.
- Create state of the art techniques to integrate tool-calling into production-serving LLMs.
- Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems.
Ideally you’d have:
- At least 1-3 years of model training, deployment and maintenance experience in a production environment.
- Strong skills in NLP, LLMs and deep learning.
- Solid background in algorithms, data structures, and object-oriented programming.
- Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
- Experience building products with LLMs including knowing the ins and outs of evaluation, experimentation, and designing solutions to get the most of the models.
- PhD or Masters in Computer Science or a related field.
Nice to haves:
- Experience in dealing with large scale AI problems, ideally in the generative-AI field.
- Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc.
- Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals.
- Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc.
- Strong written and verbal communication skills to operate in a cross functional team environment.
Machine Learning Engineer, Enterprise Research London, UK employer: Scale AI, Inc.
Contact Detail:
Scale AI, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, Enterprise Research London, UK
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in NLP and LLMs. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the AI field, especially those who work with generative AI or large-scale models. Attend relevant meetups or conferences to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Showcase your hands-on experience with cloud technologies like AWS or GCP. If you have personal projects or contributions to open-source ML projects, be ready to discuss them, as practical experience is highly valued.
✨Tip Number 4
Prepare to discuss how you've integrated human feedback into ML models in past projects. This aligns with Scale's focus on enhancing product lines and demonstrates your ability to think critically about model performance.
We think you need these skills to ace Machine Learning Engineer, Enterprise Research London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly in model training and deployment. Emphasise your skills in NLP, LLMs, and any cloud technologies you've worked with, such as AWS or GCP.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Mention specific projects or experiences that align with Scale's mission and the responsibilities of the Machine Learning Engineer role.
Showcase Your Research: If you have published research in machine learning, include this in your application. Highlight any relevant conferences where your work has been presented, as this demonstrates your expertise and commitment to the field.
Prepare for Technical Questions: Anticipate technical questions related to algorithms, data structures, and programming. Be ready to discuss your experience with deep learning frameworks and how you've applied them in real-world scenarios.
How to prepare for a job interview at Scale AI, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with NLP, LLMs, and deep learning. Bring examples of projects you've worked on, especially those involving model training and deployment in a production environment.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Think through how you would approach real-world problems, particularly those related to multi-modal content understanding and integrating human feedback into ML models.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining complex concepts in simple terms, as you'll need to work closely with clients and cross-functional teams.
✨Research the Company and Its Products
Familiarise yourself with Scale's mission and the Scale Generative AI Platform. Understanding their products and recent advancements in AI will help you align your answers with their goals and demonstrate your genuine interest.