Applied Research Engineer, Magic
Post-training
$100-550k
+ Equity
More information about location
Advanced code models for virtual coworkers
Be an early applicant
Advanced code models for virtual coworkers
21-100 employees
Be an early applicant
$100-550k
+ Equity
More information about location
21-100 employees
Company mission
To automate AI research and code generation to improve models and solve alignment more reliably than humans can alone.
Role
Who you are
- Experience with the productization and deployment of a LLM based product
- Strong general software engineering skills
- Thorough knowledge of the deep learning literature
- Experience with the post-training of LLMs
- Ability to come up with and evaluate novel research ideas
- Obsession with details, reliability, and good testing to ensure data quality and integrity
- Willingness to dive deeply into a large ML codebase to debug
What the job involves
- As a Research Engineer in post-training, you'll help develop novel techniques and datasets to maximize model performance for real-world applications, leveraging data and compute at scale
- Working closely with the applied team and customers, you’ll enable our models to operate with the best possible effectiveness in large, real-world codebases
- Research and develop innovative post-training techniques to improve models' ability to leverage additional compute and data at inference
- Partner with applied teams to enhance model capabilities to generate substantial, high-quality, functional code while optimizing for an enjoyable user experience
- Improve model capabilities for generating substantial, high-quality, functional code
- Ensure seamless integration and intuitive workflows for our users
- Create and refine continuous data feedback mechanisms to drive ongoing model improvements
- Design scalable approaches to generate synthetic datasets
Our take
Magic is a startup that uses AI to help with coding. It supplies a set of tools that can write and manage code for software projects, almost like having a smart assistant that understands programming. Interestingly, its technology can handle large amounts of code and remember details over long stretches of work.
The aim is to make things easier by automatically performing tasks such as writing new code, fixing issues and planning changes. This means developers can get help with their coding work without having to do everything manually.
The company has raised good funding from several high-profile investors. And it's also teamed up with Google Cloud to build powerful computer systems to support its AI tools. With this funding and partnership, Magic will advance its technology and work towards creating even more advanced AI in the future.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Some candidates hear
back within 2 weeks
Company
Funding (last 2 of 4 rounds)
Aug 2024
$320m
LATE VC
Feb 2024
$117m
SERIES B
Total funding: $465m
Company benefits
- Equity: Significant equity compensation
- Retirement savings: 401K with 6% salary matching
- Healthcare: Health, dental and vision insurance for you and your dependents
- Time off: Unlimited paid time off to support balance in your work and life
- Office catering: Chef-prepared lunch and dinner
- Wellbeing: Access to mental health, financial wellbeing, and telehealth programs
Company values
- Integrity: Words and actions should be aligned
- Hands-on: At Magic, everyone is building
- Teamwork: We move as one team, not n individuals
- Focus: Safely deploy AGI. Everything else is noise
- Quality: Magic should feel like magic
Company HQ
SoMa, San Francisco, CA
Articles
Leadership
Eric Steinberger
(Co-Founder & CEO)Also Founder and Chair of the Board at ClimateScience. Previously a Researcher of Deep Reinforcement Learning at Facebook AI.
Sebastian De Ro
(Co-Founder)Previously worked at FireStart for over 3 years, beginning as a Development Lead and ultimately becoming CTO. Prior to that, they were a Senior Software Engineer at ÖBB and a Lead Developer at twinformatics.
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