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Lead Engineer, Foundation Models

Labelbox

Saas

51-200

San Francisco, CA, USA

About the job

Overview:

Labelbox is the leading data-centric AI platform for building intelligent applications. Teams looking to capitalize on the latest advances in generative AI and LLMs use the Labelbox platform to inject these systems with the right degree of human supervision and automation. Whether they are building AI products by using LLMs that require human fine-tuning, or applying AI to reduce the time associated with manually-intensive tasks like data labeling or finding business insights, Labelbox enables teams to do so effectively and quickly.
Current Labelbox customers are transforming industries within insurance, retail, manufacturing/robotics, healthcare, and beyond. Our platform is used by Fortune 500 enterprises including Walmart, Procter & Gamble, Genentech, and Adobe, as well as hundreds of leading AI teams. We are backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures (Google's AI-focused fund), Databricks Ventures, Snowpoint Ventures and Kleiner Perkins.
About The Role
As the Foundation Models Lead, you will lead research and development of applying foundation models to various real world customer problems. You will be responsible for prototyping and developing production grade tools for fine tuning and alignment with human or AI feedback. Your comprehensive expertise in machine learning, natural language processing, and deep learning, and how various Foundation Models embody and excel at these technologies will be essential in driving the success of our AI initiatives in terms of roadmap definition, architecture decisions and superb execution, delivering products that meet the needs of our customers.
About You

Degree in Computer Science, Machine Learning, or a related field.
Proven experience in developing and implementing large-scale systems that integrate with Foundation Models for real-world applications.
Working knowledge of machine learning algorithms, natural language processing, and deep learning frameworks.
Experience with various types of foundation models and multi-modal models.
Proficiency in programming languages such as Python, Typescript, or Java.
Experience working with cloud computing platforms and data processing technologies.
Excellent communication and collaboration skills.
Strong creativity, problem-solving ability, attention to detail.

Your Day to Day

Conduct feasibility studies and prototype development for new applications leveraging foundation models.
Evaluate models best suited for the applications we want to support, implement hosting, inferencing and evaluating these models in our product suite, working closely with the broader engineering and product teams.
Guide customers and the broader Labelbox community with best practices in AI using Foundation Models through meetings, PoC applications, webinars, blog posts, etc.
Oversee the adaptation and fine-tuning of foundation models to suit specific application requirements.
Engage with stakeholders, including customers, to understand their needs, gather requirements, and provide expert advice on AI-driven solutions.
Monitor the performance of deployed models and implement enhancements and optimizations as needed.
Stay abreast of industry trends, emerging technologies, and advancements in foundation models and their applications. Analyze, assess and incorporate technologies coming out of various AI research labs.
Contribute to technical documentation, research publications, blog posts, and presentations at conferences and forums.

Engineering at Labelbox
We build a comprehensive platform and end-to-end tool suite for AI system development. We believe in providing the best user experience at scale with high quality. Our customers use our platform in production environments, daily, to build and deploy AI systems that have a real positive impact in the world.
We believe in collaborative excellence and shared responsibility with decision making autonomy wherever possible. We strive for a great developer experience with continuous fine tuning. How we work is one of the cornerstones of engineering excellence at Labelbox.
We learn by pushing boundaries, engaging in open debate to come up with creative solutions, then committing to execution. We continuously explore and exploit new technologies, creating new and perfecting existing techniques and solutions. Making customers win is our North Star.
Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.
The
expected annual base salary range for United States-based candidates
is $170,000 - $215,000. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.
Excel in a Hub-centric Remote Model.
We’re committed to excellence and understand the importance of bringing our talented people together. While we continue to embrace remote work, we’ve transitioned to a Hub-Centric Remote Model with a focus on nurturing collaboration and connection within our dedicated hubs in the San Francisco Bay Area, New York City Metropolitan Area, Miami-Fort Lauderdale Area, and Warsaw, Poland. We encourage asynchronous communication, autonomy, and ownership of your tasks, with the added convenience of hub-based gatherings.
Your Personal Data Privacy:
Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.
Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications. If you are uncertain about the legitimacy of any communication you have received, please do not hesitate to reach out to us at recruiting@labelbox.com for clarification and verification.