Aartificial intelligence, Analytical and Problem solving, Computer Vision (CV), Database, Effective communication skills, JavaScript, Large Language Models - LLMs, Machine learning techniques, OpenCV, Python Programming, SQL, SQL Server, TypeScript
Scale Spellbook is a developer platform for prompt engineering, evaluation, deployment, knowledge retrieval and more. We are looking for a strong product engineer to join our team and help us scale and grow our product. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.
Responsibilities:
Qualifications:
The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle, is $212,800-$258,121. 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.
Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.
United States
2-4 year
San Francisco, CA, USA
2-4 year
San Francisco, CA, USA
4-6 year