Machine Learning Engineer - WFH

About the Company

Adapter was founded in 2022 by Adam Ghetti and Dr. David Bader, with support from established Silicon Valley firms and individual entrepreneurs. The company focuses on making intelligent technologies powered by automation, artificial intelligence (AI), machine learning (ML), and knowledge graphs empowering, trustworthy, and useful in real-world applications.

Adapter is a small, dedicated team with members based across Austin, New York City, and the Bay Area. Its work culture combines remote work with in-person collaboration to support productivity and creativity.

About the Role

Adapter is seeking a Machine Learning Engineer to develop and deploy machine learning solutions, with a focus on fine-tuning transformer-based models through automation pipelines and implementing real-time fine-tuning pipelines in production environments.

In this role, you will work alongside designers, engineers, and other innovators on consumer applications of intelligent technologies. You will contribute to building, evaluating, deploying, and maintaining machine learning models while collaborating with cross-functional teams.

Key Responsibilities

• Use advanced technologies, including large language models (LLMs) and multimodal models, to address complex problems.
• Work with large datasets, perform data preprocessing, and engineer relevant features to improve model performance.
• Build frameworks for iterating on and evaluating model versions based on ranking, accuracy, and latency.
• Collaborate with software engineers to deploy machine learning models into production and integrate them with existing systems.
• Implement monitoring solutions to track model performance in real time.
• Perform regular model maintenance and updates as needed.
• Work with data scientists, software developers, and business analysts to understand requirements and deliver solutions.
• Stay informed about advancements in machine learning and contribute to research and development of new solutions.

Required Qualifications

• Proficiency 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.
• Proficiency with machine learning libraries such as PyTorch and TensorFlow.
• At least 3 years of experience in a similar role, focused on developing and deploying machine learning models in production environments.

Preferred Qualifications

• Experience optimizing models for size, cost, and latency is a plus.
• Startup experience is a plus.

Compensation

United States remote pay range: $180,000–$225,000 USD.

Full compensation packages are based on candidate experience and certifications.

Benefits and Work Culture

• Early-stage equity.
• Generous paid time off (PTO).
• A work culture that supports both remote work and in-person collaboration.

Location and Work Arrangement

Remote position open to candidates in the United States. Adapter also maintains an in-person collaborative culture, with team members currently based in Austin, New York City, and the Bay Area.