Utilidata

AI-powered grid edge platform
Last updated:
February 6, 2026
Company details
HQ
HEADCOUNT
25-99
ORG TYPE
Startup
SECTOR
Energy & Climate
About the company
Utilidata is an edge-AI company working with electric utilities and data centers to bring real-time intelligence to energy infrastructure. The flagship platform, Karman, is positioned as “AI at the edge” using a custom NVIDIA module, blending embedded software, cloud systems, and power-systems expertise. The company recruits heavily in senior technical roles, with a smaller set of operations and people-team hires. Public messaging focuses on mission impact, remote-first work, and benefits.
Locations and presence
Utilidata lists a Headquarters + Innovation Lab in Ann Arbor, Michigan, and operates remote-first with in-person collaboration moments (including an annual team retreat). Public profiles also reference Providence, Rhode Island in the company’s footprint, reflecting the company’s historical base and ongoing presence in the region.
Palpable Score
57.6
/ 100
Utilidata looks like a serious employer for compensation basics and benefits, and some job ads show unusually clear pay-range and “internal compensation bands” language. The limiting factor is access: visible hiring skews senior, and the company does not present a repeatable early-career pipeline or outcomes proof beyond small-sample reviews.
Pillar 1: Early-career access

Score

8.0
/ 20
  • The company’s live openings skew toward Senior and Principal titles across engineering and product, which reduces realistic 0–3 year entry points.
  • Utilidata shows “Intern” and “Associate” signals on public channels, but recent official openings do not clearly translate those into a consistent student or new-grad intake.
  • The company does not publish a dedicated early-careers page for internships, apprenticeships, or graduate rotations, so entry-level access looks occasional rather than recurring.

Pillar 2: Hiring fairness and transparency

Score

12.3
/ 20
  • The company uses a structured ATS with consistent job formatting and a clear “Current Openings” list, which is a baseline fairness signal.
  • Utilidata job descriptions often include concrete sections on commitments, work location expectations (remote vs onsite), and role scope, which reduces ambiguity for first-time applicants.
  • The company does not publish a candidate-facing hiring process guide (stages, timelines, task expectations, feedback norms), so applicants still have to guess what happens after applying.

Pillar 3: Learning and support

Score

12.0
/ 20
  • The company explicitly lists “mentorship and growth opportunities” as part of the working environment in role-level content, which is a direct support signal.
  • Utilidata’s remote-first setup is paired with intentional in-person collaboration touchpoints (shared office space and an annual retreat), which can help junior onboarding when used well.
  • The company does not publicly spell out onboarding design, buddying, 1:1 cadence, or progression checkpoints for early-career hires, so support quality is hard to verify beyond statements.

Pillar 4: Pay fairness and stability

Score

14.3
/ 20
  • The company publishes salary ranges on at least some postings and ties pay to skills and “internal compensation bands,” which is better than “competitive” alone.
  • Utilidata lists tangible benefits repeatedly, including health, dental, vision, and employer-match 401(k), which supports stability for early-career candidates.
  • The company’s pay transparency is not universal across every role and level, and there is little junior-specific pay guidance, which caps confidence on entry-level fairness.

Pillar 5: Early-career outcomes

Score

11.0
/ 20
  • The company has a solid overall employee sentiment signal on Glassdoor with a majority “recommend to a friend,” but the sample size is small.
  • Utilidata also has at least one sharply negative review describing leadership and “cultural fit” risk, which is hard to ignore when there are not many reviews to balance it.
  • The company does not publish early-career outcome metrics like intern-to-offer conversion, promotion timing, or 12–24 month retention, so outcomes remain mostly unverified.

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