Machine Learning Engineer

Summary

Join Blue Rose Research, a leading progressive organization, as a Machine Learning Engineer. You will develop and deploy cutting-edge machine learning models, contributing to real-time insights for key clients. This role demands full-stack machine learning and data engineering expertise, involving deep learning, transformer models, and data wrangling. You will collaborate with a diverse team, delivering actionable guidance and contributing to innovative work. We offer a competitive salary, comprehensive benefits, and a supportive remote work environment with an option for in-person collaboration. The position requires strong technical skills, experience with deep learning pipelines, and a passion for data science.

Requirements

• Has 2+ years of professional data engineering and/or machine learning experience
• Has significant experience with applied statistics and data modeling. Has developed strong instincts about how to select the right modeling approach for a problem, tune models, evaluate model performance, and diagnose and debug modeling issues
• Has experience with SQL and relational databases. Can quickly orient themselves to a new dataset, perform exploratory analysis, spot data quality issues, and justify decisions about how to handle imperfect data
• Has experience building and owning production-level deep learning pipelines using real-world data, and deploying models for both real-time interactive use and batch processing
• Is a strong Python programmer, and is familiar with standard software development tools and best practices, including cloud deployment, dependency management and versioning, and debugging cutting-edge libraries with incomplete documentation
• Has experience with NLP and training transformer ML models using PyTorch, or similar tools like TensorFlow/JAX
• Candidates must be authorized to work lawfully in the United States

Responsibilities

• Train, debug, and optimize deep learning runs on our GPU servers, and find new ways to increase model accuracy on both small and large datasets
• Conduct deep learning experiments, do feature engineering, and contribute new ideas to improve our core data science approach
• Work with a variety of datasets and survey results, clean and preprocess data, and figure out which models and loss functions are most appropriate for a given problem
• Construct agentic workflows using off-the-shelf and custom fine-tuned LLMs
• Augment agentic workflows with embedding databases
• Deliver actionable guidance to important internal stakeholders, helping them understand nuances of the model output
• Build subject matter context and think critically about what the data is saying, to understand what’s a real trend versus what’s a potential bug

Preferred Qualifications

• Experience with Agentic workflows, vector embeddings, and RAG systems
• Is familiar with cloud services, distributed systems, and other DevOps tools (Docker, Kubernetes, Terraform, etc)
• Thrives in multi-disciplinary teams working with engineers, statisticians and political experts. Is excited about working with less technical stakeholders and seeing how their work impacts real-world decision making
• Willingness to engage with the wider progressive political ecosystem and develop domain knowledge in addition to technical insight
• Has strong oral and written communication skills, especially in a remote environment
• Is a kind person and a team player who contributes to a warm working environment

Benefits

• Competitive salary
• Medical, dental, and health benefits
• Remote work