Overview: Our Mission at Magic
At Magic, we are on a bold quest to create safe Artificial General Intelligence (AGI) that accelerates humanity’s progress in tackling the world’s most pressing challenges. We are driven by the belief that the safest and most effective path to AGI involves a fusion of advanced techniques—automating research, enhancing code generation, and refining model alignment. Our innovative approach incorporates frontier-scale pre-training, domain-specific reinforcement learning, ultra-long context, and cutting-edge test-time compute to achieve breakthroughs that are beyond human capability alone.
About the Role: What You'll Be Doing
As a Research Engineer at Magic, you will play a pivotal role in shaping the future of AI. Your responsibilities will include training, evaluating, and deploying large AI models, developing new test-time compute techniques, and building expansive datasets. Additionally, you’ll be at the forefront of prototyping groundbreaking research and product ideas.
Here’s a glimpse of what you might work on:
Optimize Inference Throughput: Enhance the performance of novel model architectures to handle real-world applications efficiently.
Train Trillion-Parameter Models: Work on large GPU clusters to develop and fine-tune some of the largest AI models ever created.
Curate Post-Training Datasets: Improve targeted capabilities by selecting and refining datasets after model training.
Build Internet-Scale Data Pipelines: Develop and manage data pipelines and crawlers to support our extensive research needs.
Design and Prototype Model Architectures: Innovate and refine new AI model designs to push the boundaries of what’s possible.
Contribute to Cutting-Edge Research: Engage in research across various domains including long-context, test-time compute, and reinforcement learning.
What We’re Looking For: Are You a Fit?
We seek individuals with a strong foundation in software engineering and deep learning. If you are passionate about research, have experience with large-scale model training, and excel in handling complex systems, you might be the perfect fit for our team.
Ideal candidates will have:
Strong General Software Engineering Skills: Proficiency in coding and problem-solving across different platforms.
In-Depth Knowledge of Deep Learning: Familiarity with the latest in deep learning literature and techniques.
Experience with LLMs: Hands-on experience with the pre- and post-training processes for large language models.
Research Idea Generation: Ability to conceive and critically evaluate new research ideas.
Large Distributed Systems Experience: Comfort with managing and optimizing large-scale distributed systems.
Handling Large ETL Workloads: Skill in dealing with extensive data extraction, transformation, and loading tasks.
At Magic, we value not just technical prowess but also quick learning and resilience. We are a place where high-potential individuals can excel and make a significant impact.
Our Culture: What Drives Us
At Magic, our culture is the cornerstone of our success. We are guided by principles that foster excellence and innovation:
Integrity: Our words and actions are aligned, building trust within our team and with our stakeholders.
Hands-On: Everyone at Magic is directly involved in building and shaping our future.
Teamwork: We function as one cohesive team, with a collective focus on our mission.
Focus: Our primary goal is the safe deployment of AGI; we keep distractions to a minimum.
Quality: Our work should embody the magic that drives us—innovative, impactful, and extraordinary.
Compensation and Benefits: What We Offer
We recognize and reward talent with a comprehensive compensation package:
Annual Salary Range: $100K - $900K, based on experience and expertise.
Equity: A significant component of your total compensation, reflecting your stake in our success.
401(k) Plan: Includes 6% salary matching to help you plan for the future.
Health Benefits: Generous health, dental, and vision insurance for you and your dependents.
Unlimited Paid Time Off: Enjoy the flexibility to take time off as needed to maintain work-life balance.
Work Options: Choose to work in-person in San Francisco or remotely, depending on your preference.
Visa Sponsorship and Relocation Stipend: Support for moving to San Francisco if needed.
A Dynamic Team: Join a small, fast-paced team that is highly focused on achieving our ambitious goals.
Are you ready to join us in making a difference? Apply now to become a Research Engineer at Magic and be a part of a team that’s redefining the future of AI.
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