Senior Software Engineer - Data Infrastructure

About the role

We are looking for infrastructure engineers with expertise in scaling open-source data infrastructure to join the Data & ML infra group. This role will work across the entire data lifecycle (collection, ingestion, storage, querying, retrieval) and work directly with all business units across the company to design and develop both external and internal products. Handling massive volumes of data for Applied Intuition's platform needs is a critical area and we are looking for someone who can be hands-on in supporting our data products and verticals across the company. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture. At Applied Intuition, you will: Scale infrastructure to support all deployment types (cloud, hybrid, on-prem) and across regions Be involved in the end to end data lifecycle, from the external-facing product to the underlying platform and infrastructure for it Build features to tune processing pipeline for fast data ingestion and indexing depending on customer's needs and workloads Enable product workflows that expose performant query interfaces and offer easy-to-use integration hooks Develop and deploy high-quality software using modern tooling and frameworks, especially open-source technologies We're looking for someone who has: A Bachelor's degree in Computer Science, Software Engineering, or equivalent 3+ years of professional experience Experience with large-scale open source data technologies (Spark, Kafka, Hudi, Flyte, etc.) Experience with containerization and other modern software development workflows Knowledge of the open source landscape with judgment on when to choose open source versus build in-house

Requirements

• Expertise with modern programming languages (Python, C++, GoLang, Scala, etc.)
• Experience with other open-source data technologies not listed above
• Expertise with Kubernetes
• Experience with enterprise software, including on-prem and/or cloud environments
• Deep knowledge of data quality, data profiling and cleansing techniques
• Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $153,000 - $222,000 USD annually.
• Don't meet every single requirement? If you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
• Applied Intuition is an equal opportunity employer and federal contractor or

Benefits

Additional Information

About Applied Intuition Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company's solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co . We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.

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