Added 2 days agoScale AISan Francisco$216K-$270K / year
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 products include the Generative AI Data Engine, SGP, Donovan, and others that power 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.
At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. 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.
You will:
Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
Collaborating with cross-functional teams to define, design, and deliver new features.
Proactively identifying opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
Presenting technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.
Ideally you’d have:
3+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
Show a track record of independent ownership of successful engineering projects.
Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
Experience with orchestration platforms, such as Temporal and AWS Step Functions.
Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
Nice to haves:
Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).
Experience with authentication/authorization systems (Zanzibar, Authz, etc.)
Experience scaling products at hyper-growth startups.
Excitement to work with AI technologies.
Compensation packages at Scale for eligible roles 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 and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. 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.
The base salary range for this full-time position in the location of San Francisco is:
$216,000—$270,000 USD
_PLEASE NOTE: _Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst& Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
_We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. _
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
_We comply with the United States Department of Labor's Pay Transparency provision. _
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