Software Engineer, Machine Learning

Overview

Are you passionate about advancing deep learning research and developing general human-like machine intelligence? Join us as a Software Engineer, Machine Learning. In this role, you will collaborate closely with a senior member of our research team to work on cutting-edge deep learning projects, infrastructure, and tooling.

Responsibilities

• Research Implementation: Read and implement various research papers to improve architecture efficiency, training speed, loss metrics, and fine-tuning methods.
• Experimental Design: Devise and conduct scientifically rigorous experiments to validate the effectiveness of proposed adjustments for solving Imbue’s target problems using LLMs.
• Fundamental Understanding: Enhance our knowledge of LLM fundamentals, focusing on areas such as chain-of-thought, reasoning, generalization, hallucination, and grokking.
• Hyperparameter Optimization: Utilize our existing framework to perform hyperparameter sweeps, and contribute to the development of new features for the sweep code.
• Infrastructure Collaboration: Work with infrastructure engineers to develop monitoring systems, informative logging, and maintenance guides for long-running experiments.
• Dataset Improvement: Collaborate with data and product engineers to identify and implement improvements in our training and evaluation datasets.
• Model Performance: Conduct scientific research and development to create LLM models that perform effectively in practical applications.
  
  

Example Projects

• Implement improvements from recent research papers to enhance model architecture and training methods.
• Design and run experiments to test the impact of new techniques on LLM performance.
• Investigate and optimize aspects of LLM behavior such as reasoning and generalization.
• Perform hyperparameter sweeps and contribute to the development of new features in our hyperparameter tuning framework.
• Develop robust monitoring and logging systems for long-running experiments in collaboration with infrastructure engineers.
• Improve the quality and effectiveness of training and evaluation datasets in partnership with data and product engineers.
  
  

Requirements

• Python Proficiency: Highly comfortable writing Python code.
• PyTorch Experience: Familiar with PyTorch and experienced in training deep neural networks.
• Open Source Enthusiasm: Excited to work on and contribute to open-source projects.
• Best Practices: Passionate about engineering best practices and maintaining high-quality code standards.
• Self-Direction: Able to work independently and manage your own tasks effectively.
• Execution Excellence: Demonstrated ability to get things done efficiently and effectively.
  
  

Required Skills

• Python programming
• PyTorch and training deep neural networks
• Open source code development
• Conducting experiments and testing research-based improvements
• Understanding of LLM knowledge and inference
• Working with infrastructure for monitoring and logging
• Improving training and evaluation datasets
  
  

Benefits:Benefits

• Competitive Salary: $175,000 - $325,000 annually.
• Health Insurance: Comprehensive medical, dental, and vision coverage.
• Retirement Plans: 401(k) plan with company matching.
• Paid Time Off: Generous PTO policy including vacation, sick leave, and holidays.
• Professional Development: Opportunities for continuous learning and career growth, including access to conferences, workshops, and online courses.
• Flexible Work Arrangements: Options for remote work and flexible scheduling to support work-life balance.
• Parental Leave: Paid parental leave for new parents.
• Wellness Programs: Access to mental health resources, wellness programs, and fitness reimbursements.
• Employee Assistance Program: Support for personal and professional issues through our EAP.
• Stock Options: Equity options to share in the company’s success.
• Commuter Benefits: Pre-tax commuter benefits for public transportation and parking.
• Technology Stipend: Annual stipend for tech equipment and home office setup.
• Company Events: Regular team-building activities, social events, and company retreats.
• Diversity and Inclusion: Commitment to fostering an inclusive and diverse workplace.