Aartificial intelligence, AWS, Cloud computing, Data structuring, Deep Learning, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, Natural Language Processing (NLP), Object-Oriented programming (OO languages), Python Programming, PyTorch, TensorFlow, Terraform, Video processing/compression
Model code and data form the foundation of an AI system. Scale’s leading end-to-end solutions for the ML lifecycle based on real-world data will continue to set the bar for the data-centric AI movement. We are looking for entrepreneurial Machine Learning Engineers to seed and grow our team. Your core focus will be on Content Understanding use cases - recommendations, discovery, marketplace trust & safety, etc. If you are excited about shaping the future of the data-centric AI movement, we would love to hear from you!
You will:
Ideally you’d have:
Nice to haves:
The salary range for our Tier 1 locations of San Francisco & New York is ~$240,000.00 - $300,000.00.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