Engineering Manager - Data Intelligence

Posted Yesterday
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Sunnyvale, CA, USA
In-Office
204K-343K Annually
Mid level
Hardware • Industrial
The Role
Lead and grow an engineering team building data quality systems, intelligent labeling workflows, and large-scale data mining to surface edge cases. Drive integration of foundation models, set technical direction and roadmaps, partner with research and infrastructure teams, and hire and mentor engineers to scale high-fidelity labels and accelerate ML iteration for autonomy.
Summary Generated by Built In
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.

About the role

As an Engineering Manager on the Data Intelligence team, you'll lead a world-class group of engineers focused on revolutionizing how we produce, curate, and leverage high-quality data to accelerate autonomy development. Your team will work across three key areas: Data Quality, where we build systems to measure, validate, and improve the integrity of our datasets; Labeling Workflows, where we design intelligent annotation pipelines that combine human expertise with AI-powered automation; and Data Mining, where we surface rare, high-value driving scenarios from massive multi-modal fleet data. You'll drive the adoption of foundation models and cutting-edge AI techniques to scale these capabilities, setting technical direction and team goals that align with our model development, safety, and deployment milestones.

At Applied Intuition, you will:
  • Grow and manage a team of world-class engineers with the goal of delivering high-quality, well-labeled data and identifying critical edge cases for autonomy

  • Prioritize development across data quality systems, intelligent labeling workflows, and large-scale data mining infrastructure

  • Lead the integration of foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery

  • Evolve our data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles

  • Set team goals and roadmap in alignment with training, evaluation, and deployment requirements

  • Partner with research, autonomy, and data infrastructure teams to ensure high-quality, relevant, and diverse data is powering our models

  • Drive hiring, mentoring, and growth for a high-performing, mission-driven team

We’re looking for someone who has:
  • 3+ years of engineering management experience

  • Passion for building and leading high-performing teams

  • Experience building data quality systems, labeling pipelines, or annotation platforms at scale

  • Familiarity with modern ML infrastructure and data-centric AI approaches

  • Understanding of how foundation models can be applied to automate data workflows

  • Solid track record of building and deploying products

Nice to have:
  • Direct experience with foundation models, including LLMs and VLMs, for data automation tasks

  • Background in autonomous driving or robotics perception

  • Experience with active learning, auto-labeling, or human-in-the-loop ML systems

  • Familiarity with 3D perception data (camera, lidar, radar)

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

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: $204,000 - $343,000 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 subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.

Skills Required

  • 3+ years of engineering management experience
  • Passion for building and leading high-performing teams
  • Experience building data quality systems, labeling pipelines, or annotation platforms at scale
  • Familiarity with modern ML infrastructure and data-centric AI approaches
  • Understanding of how foundation models can be applied to automate data workflows
  • Solid track record of building and deploying products
  • Direct experience with foundation models, including LLMs and VLMs, for data automation tasks
  • Background in autonomous driving or robotics perception
  • Experience with active learning, auto-labeling, or human-in-the-loop ML systems
  • Familiarity with 3D perception data (camera, lidar, radar)
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The Company
HQ: Cleveland, OH
3,411 Employees
Year Founded: 1923

What We Do

Founded in 1923, Applied Industrial Technologies is a leading value-added distributor and technical solutions provider of industrial motion, fluid power, flow control, automation technologies, and related maintenance supplies. Our leading brands, specialized services, and comprehensive knowledge serve MRO and OEM end users in virtually all industrial markets through our multi-channel capabilities that provide choice, convenience, and expertise.

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