Give your model, agent, or app a mind. Connect your data and Adapter builds a living understanding of your world, with every answer cited to its source. Backed by GV.
About the role
You will partner with a brilliant team of designers, engineers, and innovators and will be at the cutting edge of some of the most interesting consumer use-cases for intelligent technologies.
What they're looking for
- Experience with optimizing models for size, cost, and latency is a plus
- Proficient in designing, developing, and operating fine-tuning pipelines in production environments
- Experience with large-scale data processing and distributed systems
- Strong programming skills in Python, and proficiency in machine learning libraries such as PyTorch, Tensorflow etc
- 3+ years of experience in similar role, focus on developing and deploying ML models in production environments
- Startup experience is a plus
More about this role
The widespread adoption of intelligent technologies powered by automation, AI, ML, and knowledge graphs is accelerating. As these technologies become increasingly accessible, our aim is to make their capabilities empowering, trustworthy, and useful to real people in the real world.
Adapter was founded in 2022 by Adam Ghetti and Dr. David Bader , with the support of some of the most esteemed Tier 1 Silicon Valley firms and individual entrepreneurs. We are a small but dedicated team, currently working towards solving a significant problem. We recognize the importance of being early movers in this field, and have assembled a well-supported and passionate team to do so.
We are looking for a Machine Learning Engineer who will play a critical role in fine-tuning transformer-based models using automation pipelines and implementing real-time fine-tuning pipelines in production environments.
You will partner with a brilliant team of designers, engineers, and innovators and will be at the cutting edge of some of the most interesting consumer use-cases for intelligent technologies.
We have established a culture that promotes both remote work and in-person collaboration, with team members...
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