Staff Machine Learning Engineer, Foundation Models
Scale’s Foundational ML team conducts research on new foundational capabilities, with the goal of innovating models and algorithms that unlock net-new capabilities for Scale’s applied-ML teams and the broader AI community. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s Generative AI team focused on building models to accelerate and optimize AI adoption for some of the largest companies in the world.
At Scale, our research is driven by product needs. Your focus will be on developing new foundational models, algorithms, and forms of supervision for Generative AI. You will lead writing, publishing, and adoption of your work internally with applied teams. You will be involved end-to-end from the inception and planning of new research agendas. You'll be creating high quality datasets, implementing models and associated training and evaluation stacks, producing high caliber publications in the form of peer-reviewed journal articles, blogs, white papers, and internal presentations & documentation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!
- Evaluate, adapt, and develop new state of the art language and/or multimodal foundation models
- Work with applied ML and product teams to identify opportunities for service improvement or new capabilities
- Explore approaches that integrate human feedback and assisted evaluation into existing product lines
- Work closely with internal customers to prototype, build, and integrate your models into production service
Ideally you’d have:
- A track record of high-caliber publications in peer-reviewed machine learning venues (e.g. NeurIPS, ICLR, ICML, EMNLP, CVPR, AAAI etc.)
- At least 3 to 5 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 cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
- Strong high-level programming skills (e.g., Python), frameworks and tools such as Pytorch lightning, kuberflow, TensorFlow, transformers, etc.
- Strong written and verbal communication skills to operate in a cross functional team environment and to broadcast your work efficiently and with splash
Nice to haves:
- Experience in dealing with large scale AI problems, ideally in the generative-AI field.
- Demonstrated expertise in large language models for diverse real-world, production applications, e.g. question-answering, generation, classification, etc.
The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle, is $240,000-$280,000. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
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 machine learning can build innovative products. Our products provide access to human-powered data for hundreds of use cases and are used by industry leaders such as Open AI, Lyft, Meta, GM, Samsung, Airbnb, NVIDIA, and many more. We’ve recently raised $325 million in Series E funding at a valuation of $7B+ and 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. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
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