AI is becoming vitally important in every function ofour society. At Scale, our mission is to accelerate the developmentof AI applications. For 8 years, Scale has been the leading AI datafoundry, helping fuel the most exciting advancements in AI,including generative AI, defense applications, and autonomousvehicles. With our recent Series F round, we’re accelerating theusage of frontier data and models by building complex agents forenterprises around the world through our Scale Generative AIPlatform (SGP). The SGP ML team works on the front lines of this AIrevolution. We interface directly with clients to build cuttingedge products using the arsenal of proprietary research andresources developed at Scale. As an ML Engineer, you’ll work withclients to train ML models to satisfy their business needs. Yourwork will range from training next-generation AI cybersecurityfirewall LLMs to training foundation genomic models makingpredictions about life-saving drug proteins. Having a deepcuriosity about the hardest questions about LLMs will also motivatevarious research opportunities on how to apply ML to the forefrontof enterprise data. If you are excited about shaping the future ofthe modern AI movement, we would love to hear from you! You will: -Train state of the art models, developed both internally and fromthe community, in production to solve problems for our enterprisecustomers. - Work with product and research teams to identifyopportunities for ongoing and upcoming services. - Exploreapproaches that integrate human feedback and assisted evaluationinto existing product lines. - Create state of the art techniquesto integrate tool-calling into production-serving LLMs. - Workclosely with customers - some of the most sophisticated MLorganizations in the world - to quickly prototype and build newdeep learning models targeted at multi-modal content understandingproblems. Ideally you’d have: - At least 1-3 years of modeltraining, deployment and maintenance experience in a productionenvironment - Strong skills in NLP, LLMs and deep learning - Solidbackground in algorithms, data structures, and object-orientedprogramming - Experience working with a cloud technology stack (eg.AWS or GCP) and developing machine learning models in a cloudenvironment - Experience building products with LLMs includingknowing the ins and outs of evaluation, experimentation, anddesigning solutions to get the most of the models - PhD or Mastersin Computer Science or a related field Nice to haves: - Experiencein dealing with large scale AI problems, ideally in thegenerative-AI field - Demonstrated expertise in largevision-language models for diverse real-world applications, e.g.classification, detection, question-answering, etc. - Publishedresearch in areas of machine learning at major conferences(NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals - Stronghigh-level programming skills (e.g., Python), frameworks and toolssuch as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc. -Strong written and verbal communication skills to operate in across functional team environment #J-18808-Ljbffr
