(Only 24h Left) Machine Learning Engineer, EnterpriseResearch London, UK...

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 #J-18808-Ljbffr