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Machine Learning Engineer at adapter | United States

AdapterUnited States - Remote
Remote Full-time $180K/yr - $225K/yr

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Experience Level

Experience

Qualifications

Ideal candidates will have a strong background in machine learning, data science, and software engineering. Proficiency in programming languages such as Python or Java, experience with machine learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with cloud computing platforms (AWS, GCP) are essential. A Bachelor's degree in Computer Science, Data Science, or a related field is preferred, along with a passion for tackling real-world challenges through intelligent technology.

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.

About Adapter

Adapter is a forward-thinking technology firm dedicated to democratizing intelligent technologies for everyday use. With a vibrant team and strong backing from leading investors, we are committed to innovation and excellence in the AI landscape.

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