Machine Learning Engineer

Adapter is a company focused on making intelligent technologies accessible and useful. They are seeking a Machine Learning Engineer to fine-tune transformer-based models and implement real-time pipelines in production environments, collaborating with a team of designers and engineers.

Responsibilities:

• Use the latest cutting edge technologies such as LLMS, multimodal models to handle complex problems
• Work with large datasets, perform data preprocessing, and engineer relevant features to enhance model performance
• Build frameworks that allow us to iterate and evaluate model versions (ranking, accuracy, latency)
• Deploy Models at Scale: Collaborate with software engineers to deploy machine learning models into production, ensuring seamless integration with existing systems
• Monitoring and Maintenance: Implement monitoring solutions to track model performance in real-time and perform regular maintenance and updates as needed
• Collaboration: Work closely with cross-functional teams, including data scientists, software developers, and business analysts, to understand requirements and deliver impactful solutions
• Research and Innovation: Stay abreast of the latest advancements in machine learning and contribute to the research and development of innovative solutions

Requirements:

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