Scale’s AI Infrastructure team supports both R&D and applied Generative AI initiatives, driving breakthroughs in areas of post-training research such as AI safety, agents, and evaluating state-of-the-art model performance.
As a Data Infrastructure Engineer on the AI Infrastructure team, you will design, build, and scale the data platform that powers all R&D and applied ML initiatives at Scale. Collaborating closely with product engineering, platform engineering, and ML researchers, you will build robust and easy-to-use APIs and data pipelines. Your work will play a critical role in advancing frontier ML research, accelerating the data sales cycle, and improving data quality - all while optimizing infrastructure costs.
You will:- Design, implement, and maintain scalable data platforms to support diverse R&D and applied ML workloads.
- Partner with ML researchers, product engineers, and operations teams to align data infrastructure with organizational goals.
- Collaborate with ML researchers to build data access tools that help advance the state of frontier post-training research.
- Participate in our team’s on call process to ensure the availability of our services.
- Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.
- 2+ years of experience in building and operating large-scale distributed data systems that support ML workloads.
- Expertise in modern data platform technologies.
- Experience working with standard containerization & deployment technologies like Kubernetes, Helm, Terraform, Docker, etc.
- Strong problem solving skills and the ability to work effectively in a fast paced, dynamic environment.
- Familiarity with ML development tools such as PyTorch, HuggingFace, or Weights & Biases.
- Experience with a variety of storage systems: object (S3), document (MongoDB), relational (Postgres), and distributed (Redis, Elasticsearch).
- Exposure to orchestration platforms like Temporal, Airflow, or AWS Step Functions.
- Experience supporting post-training workflows such as evaluation, fine-tuning, and RLHF in LLM systems.
- Experience working in a fast-moving startup or high-scale ML infra environment.
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, determined by work location and additional factors, including job-related skills, experience, 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.
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, Cisco, DLA Piper, 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 [email protected]. 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.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Top Skills
Similar Jobs
What you need to know about the Boston Tech Scene
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
