Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our Generative AI Data Engine powers the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

We’re looking for entrepreneurial Software Engineers to join our team. In this role, you'll be given the opportunity to build any of these products to meaningfully drive millions of dollars in revenue. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

The ideal person is a natural entrepreneurial engineer who can take an ambiguous scope and lead the execution of outcomes, doing what it takes to hit them incl coding, talking to customers, defining requirements, etc. We strongly believe the best engineers own outcomes and deeply understand customer problems. This tweet by Greg Brockman summarizes it well:

https://twitter.com/gdb/status/1514291063233474560

You’re excited about solving customer problems, and you pick the technologies and tactics that balance speed, function, and long-term robustness.

You will:

• Own large new areas within our product
• Work across backend, frontend, and interacting with LLMs and/or other ML models
• Deliver experiments at a high velocity and level of quality to engage our customers
• Work across the entire product lifecycle from conceptualization through production
• Be able, and willing, to multi-task and learn new technologies quickly
• Collaborating with cross-functional teams to define, design, and ship new product features and experiences.

Ideally you’d have:

• 5 years of full-time engineering experience, post-graduation
• Proficiencies in one or more of Python, Node, React, Next.js and MongoDB
• Solid background in algorithms, data structures, and object-oriented programming.
• Experience scaling products at hyper-growth startups
• Excitement to work with AI technologies
• Strong written and verbal communication skills
• Strong problem-solving skills, and be able to work independently or as part of a team.

Nice to haves:

• Strong knowledge of software engineering best practices.
• Have experience with AI platforms and technologies, including generative models and LLMs.
• Experience building ML infrastructure and AI-powered solutions.

The base salary range for this full-time position in our hub locations of San Francisco or NYC is $153,000 - $215,000. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.