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Software Engineer, Machine Learning

Unreal Gigs

San Francisco, california


Job Details

Full-time


Full Job Description

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.

Requirements

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.

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