Software Engineer, Magic

$200-550k

+ Equity is a significant part of total compensation, in addition to salary

Mid and Senior level

San Francisco Bay Area

More information about location

Advanced code models for virtual coworkers

Open for applications

Advanced code models for virtual coworkers

21-100 employees

B2BArtificial IntelligenceDeep TechSaaS

Open for applications

$200-550k

+ Equity is a significant part of total compensation, in addition to salary

Mid and Senior level

San Francisco Bay Area

More information about location

21-100 employees

B2BArtificial IntelligenceDeep TechSaaS

Company mission

To automate AI research and code generation to improve models and solve alignment more reliably than humans can alone.

Job

Company

Role

Who you are

Strong software engineering fundamentals
High ownership and comfort operating in ambiguous problem spaces
Experience building production systems at scale
Ability to reason clearly about trade-offs between quality, performance, and cost
Strong technical judgment and bias toward shipping
Track record of turning complex technical problems into working systems

What the job involves

As a Software Engineer at Magic, you will work on core systems or product surfaces that directly determine model capability and user experience
This role can map onto Pre-training Data, RL Research & Environments, or Product, depending on background and strengths. Across all placements, the expectation is end-to-end ownership: defining problems, implementing solutions, shipping to production, and iterating based on real outcomes
Magic’s long-context models introduce unique technical challenges — internet-scale data acquisition, long-horizon post-training loops, and product workflows that make complex model behavior understandable and controllable
You will operate close to these constraints, building systems that are both technically rigorous and production-ready
This role can evolve into deeper specialization in data systems, post-training capability development, or product engineering leadership, depending on strengths and interests
Build and scale large distributed data pipelines for pre-training
Design filtering, mixture, and dataset versioning systems
Develop post-training datasets, evaluation frameworks, and reward pipelines
Run ablations that translate capability goals into measurable improvements
Build end-to-end product surfaces that integrate deeply with the model
Design APIs, backend services, and frontend workflows for AI-first experiences
Improve reliability, observability, and performance of production systems

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 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 is set to advance its technology and work towards creating even more advanced AI in the future.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 4 rounds)

Aug 2024

$320m

LATE VC

Feb 2024

$117m

SERIES B

Total funding: $465m

Company benefits

Salary and equity: Competitive salary with 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 HQ

SoMa, San Francisco, CA

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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