In 2012, Lambda started with a crew of AI engineers publishing research at top machine-learning conferences. We began as an AI company built by AI engineers. That hasn’t changed. Today, we’re on a mission to be the world’s top AI computing platform. We equip engineers with the tools to deploy AI that is fast, secure, affordable, and built to scale. Whether they need powerhouse GPU hardware on-site or the flexibility of cloud-based solutions, we’ve got the horsepower to make it happen. Lambda’s AI Cloud has been adopted by the world’s leading companies and research institutions including Anyscale, Rakuten, The AI Institute, and multiple enterprises with over a trillion dollars of market capitalization. Our goal is to make computation as effortless and ubiquitous as electricity.

If you’d like to build the world’s best deep learning cloud, join us.

• Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

SALARY RANGE INFORMATION

Based on market data and other factors, the annual salary range for this position is $135,000-$200,000. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

• Internal Tools Development: Design, build, and maintain scalable, robust, and efficient internal tools that accelerate Lambda’s business processes.
• Support Business Teams: Use your familiarity with internal and external API’s and software engineering to support stakeholder requests and design and improve internal systems
• System Architecture: You’ll work with product engineers and system admins to design, document, and build flows between systems and infrastructure. You will also be a technical subject matter expert and recommend improvements to our internal technology stack
• Quality & Reliability: Ensure the accuracy and consistency of data across multiple systems, performing regular data quality assessments. Implement testing, CICD and IT General Controls to ensure security and reliability of data flows.
• Collaboration: Work closely with business leaders, analysts, and other stakeholders to understand requirements and deliver appropriate solutions. This will include participating early in product-design discussions, and staying involved with teams across the company.
• Automation & Optimization: Automate manual processes and continuously optimize systems for performance, cost efficiency, and scalability.
• Technology Evaluation: Stay up-to-date with the latest industry trends, tools, and technologies to improve data engineering practices and infrastructure.
• Mentorship: Provide technical leadership and mentorship to junior engineers, analysts, and business users, sharing best practices and fostering a collaborative team environment.