Software Engineer - Post-training Data

Magic; San Francisco (CA); On-site; USD 100,000 - 550,000; Full time

Benefits offered by this job

Annual salary range: $100K - $550K

Equity compensation

401(k) plan with 6% salary matching

Generous health, dental and vision insurance

Unlimited paid time off

Visa sponsorship and relocation stipend

Job summary

Dormont Manufacturing Co is hiring a Software Engineer to work on post-training data infrastructure. This role involves developing efficient data pipelines and collaborating with teams to gather diverse datasets at scale.

The ideal candidate will demonstrate attention to detail and the ability to write reliable, well-tested code. Benefits include competitive salaries, equity, and comprehensive health plans.

Qualifications

• Proven ability to write reliable and well-tested code.
• Experience in developing and maintaining data pipelines.
• Strong skills in processing and understanding large datasets.

Responsibilities

• Develop creative methods to obtain post-training datasets.
• Generate reliable synthetic datasets.
• Implement and test data pipelines to manage workloads.

Skills

Attention to detail

Data quality commitment

End-to-end data pipeline versatility

Ability to quickly learn new tools

Grit to tackle tough challenges

Job description

Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference‑time compute to achieve this goal.

About the role:

As a Software Engineer working on our post‑training data infrastructure, you write efficient and robust data pipelines and work with the research and Applied teams to devise strategies for gathering and maintaining specific, diverse datasets at scale.

What you might work on:

• Develop creative ways to obtain post‑training datasets teaching the model targeted capabilities.

• Develop creative ways to reliably generate synthetic datasets

• Iterate on filtering and scoring heuristics for a post‑training dataset

• Contribute to our data infrastructure by implementing, maintaining and testing data pipelines serving workloads across scales from gigabytes to 100s of petabytes

What we’re looking for:

• Extreme attention to detail and commitment to data quality.

• Ability to write reliable, well‑tested code and quickly learn new tools, programming languages or frameworks needed for a given job.

• Versatility in end‑to‑end data pipelines, from scraping to processing.

• High intellectual agility and grit to tackle tough challenges.

Magic strives to be the place where high‑potential individuals can do their best work. We value quick learning and grit just as much as skill and experience.

Our culture:

• 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

Compensation, benefits and perks (US):

• Annual salary range: $100K - $550K

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

• 401(k) plan with 6% salary matching

• Generous health, dental and vision insurance for you and your dependents

• Unlimited paid time off

• Visa sponsorship and relocation stipend to bring you to SF, if possible

• A small, fast‑paced, highly focused team