About the job
About Us:
As intelligent technologies fueled by automation, AI, ML, and knowledge graphs become more prevalent, we at Adapter are on a mission to make them accessible, empowering, and trustworthy for real people in the real world.
Founded in 2022 by Adam Ghetti and Dr. David Bader, with backing from top-tier Silicon Valley firms and visionary entrepreneurs, Adapter is a small yet passionate team dedicated to tackling significant challenges in this evolving landscape.
Your Role:
We are searching for a talented Machine Learning Engineer to join our team. In this pivotal role, you will refine transformer-based models utilizing automation pipelines and implement real-time fine-tuning pipelines in production settings.
Collaborate with a dynamic group of designers, engineers, and innovators, engaging in some of the most exciting consumer applications of intelligent technologies.
We foster a culture that embraces both remote work and in-person collaboration, with our team members currently located in Austin, NYC, and the Bay Area. We believe this blend maximizes productivity and creativity as we pursue our goals.
Key Responsibilities:
- Utilize cutting-edge technologies, including LLMS and multimodal models, to address complex challenges.
- Work with extensive datasets, conducting data preprocessing and feature engineering to optimize model performance.
- Develop frameworks that facilitate model iteration and evaluation (ranking, accuracy, latency).
- Deploy machine learning models at scale: Collaborate with software engineers to integrate models into production seamlessly.
- Implement monitoring solutions to track model performance in real-time, carrying out regular maintenance and updates as necessary.
- Collaborate closely with cross-functional teams, data scientists, software developers, and business analysts, to understand requirements and deliver effective solutions.
- Stay updated with the latest advancements in machine learning and contribute to innovative research and development initiatives.
