At a Glance
- Tasks: Train cutting-edge ML models and collaborate with clients to solve real-world problems.
- Company: Scale is a leading AI data foundry, driving advancements in AI across various industries.
- Benefits: Enjoy a flexible work environment, inclusive culture, and opportunities for professional growth.
- Why this job: Join the AI revolution and make a tangible impact on the future of technology.
- Qualifications: 1-3 years of experience in ML model training, strong NLP skills, and a relevant degree.
- Other info: We value diversity and provide accommodations for applicants with disabilities.
The predicted salary is between 43200 - 72000 £ 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 (e.g., 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.
About Us: At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace.
Machine Learning Engineer, Enterprise employer: Scale AI
Contact Detail:
Scale AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, Enterprise
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in NLP and LLMs. Being able to discuss recent trends or breakthroughs during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Showcase your experience with cloud technologies like AWS or GCP. Be prepared to discuss specific projects where you deployed ML models in a cloud environment, as this is crucial for the role.
✨Tip Number 3
Prepare to talk about your approach to integrating human feedback into ML models. This is a key aspect of the role, so having examples or ideas ready can set you apart from other candidates.
✨Tip Number 4
Network with professionals in the AI and ML community, especially those who have experience with generative AI. Engaging in discussions or attending relevant meetups can provide insights and connections that may help you during the application process.
We think you need these skills to ace Machine Learning Engineer, Enterprise
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, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for AI and how your background aligns with Scale's mission. Mention specific projects or experiences that demonstrate your ability to solve complex problems using ML, and how you can contribute to their team.
Showcase Relevant Projects: If you have worked on any significant projects related to generative AI or large-scale ML problems, be sure to include them in your application. Detail your role, the technologies used, and the impact of the project to showcase your hands-on experience.
Highlight Communication Skills: Since the role involves working closely with clients and cross-functional teams, emphasise your written and verbal communication skills. Provide examples of how you've successfully collaborated with others in previous roles or projects.
How to prepare for a job interview at Scale AI
✨Showcase Your Technical Skills
Be prepared to discuss your experience with model training, deployment, and maintenance. Highlight specific projects where you've worked with NLP, LLMs, or deep learning, and be ready to explain the algorithms and data structures you used.
✨Demonstrate Problem-Solving Abilities
Think of examples where you've tackled complex AI problems, especially in a production environment. Be ready to discuss how you approached these challenges and the impact your solutions had on the business.
✨Engage with the Interviewers
Since you'll be working closely with clients, strong communication skills are essential. Practice articulating your thoughts clearly and ask insightful questions about the company's projects and goals to show your genuine interest.
✨Prepare for Technical Questions
Expect technical questions related to cloud technology stacks like AWS or GCP, as well as frameworks such as TensorFlow or PyTorch. Brush up on your knowledge of these tools and be ready to discuss how you've used them in past projects.