Member of Technical Staff - Model Serving, API Backend

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February 5

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Prior Labs

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Artificial Intelligence • Data Science • SaaS

Prior Labs is a cutting-edge company focused on revolutionizing data science by building foundation models that have a deep understanding of tabular data. Aiming to bring advanced AI capabilities to the analysis of tables, Prior Labs seeks to enhance how users interact with their most valuable data format. By transforming tabular data analysis, they aspire to help individuals and businesses make better decisions and unlock insights across various sectors including healthcare and science.

2 - 10 employees

🤖 Artificial Intelligence

☁️ SaaS

📋 Description

• Black Forest Labs is a cutting-edge startup pioneering generative image and video models. • Develop and maintain robust APIs for serving machine learning models. • Transform research models into production-ready demos and MVPs. • Optimize model inference for improved performance and scalability. • Implement and manage user preference data acquisition systems. • Ensure high availability and reliability of model serving infrastructure. • Collaborate with ML researchers to rapidly prototype and deploy new models.

🎯 Requirements

• Strong proficiency in Python and its ecosystem for machine learning, data analysis, and web development • Extensive experience with RESTful API development and deployment for ML tasks • Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) • Knowledge of cloud platforms (AWS, GCP, or Azure) for deploying and scaling ML services • Proven track record in rapid ML model prototyping using tools like Streamlit or Gradio • Experience with distributed task queues and scalable model serving architectures • Understanding of monitoring, logging, and observability best practices for ML systems • Experience with frontend development frameworks (e.g., Vue.js, Angular, React) • Familiarity with MLOps practices and tools • Knowledge of database systems and data streaming technologies • Experience with A/B testing and feature flagging in production environments • Understanding of security best practices for API development and ML model serving • Experience with real-time inference systems and low-latency optimizations • Knowledge of CI/CD pipelines and automated testing for ML systems • Expertise in ML inference optimizations, including techniques such as: • Reducing initialization time and memory requirements • Implementing dynamic batching • Utilizing reduced precision and weight quantization • Applying TensorRT optimizations • Performing layer fusion and model compilation • Writing custom CUDA code for performance enhancements