lidar jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, lidar appears in 367 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning lidar, with demand share up 9.1% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
367
Demand vs prior month
up 9.1% vs the prior 4 weeks
Top role · 20.4% of skill postings
Top hiring metro
Mountain View

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Frequently asked questions about lidar

+Is lidar in demand in 2026?

Yes. lidar appears in 367 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning lidar (20.4% of all postings mentioning lidar).

+What jobs require lidar?

According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning lidar are Robotics Engineer (22.5% of that role’s postings mention lidar), Robotics Software Engineer (17.0% of that role’s postings mention lidar), Hardware Engineer (15.0% of that role’s postings mention lidar).

+What skills are commonly paired with lidar?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), lidar most often appears alongside radar, Python, C++, sensor fusion, cameras.

+Where is lidar most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring lidar are Mountain View, Sunnyvale, Santa Clara, Costa Mesa, Munich, according to the Skillenai jobs index.

+How can I keep up with new lidar content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning lidar alongside the jobs index. You can subscribe to a daily email digest of new lidar content from your Skillenai account.

+Which skills come before and after lidar?

The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.

Weekly indexed postings requiring lidar — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around lidar

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before lidar

Before lidarpython → lidar: 4 observed employer moves with this skill pairtensorflow → lidar: 3 observed employer moves with this skill pairC# → lidar: 2 observed employer moves with this skill pairMYSQL → lidar: 2 observed employer moves with this skill pairPower BI → lidar: 2 observed employer moves with this skill pairdocker → lidar: 2 observed employer moves with this skill pairBootstrap → lidar: 2 observed employer moves with this skill pairopencv → lidar: 2 observed employer moves with this skill pairlidarpython: 4 movespython4 movestensorflow: 3 movestensorflow3 movesC#: 2 movesC#2 movesMYSQL: 2 movesMYSQL2 movesPower BI: 2 movesPower BI2 movesdocker: 2 movesdocker2 movesBootstrap: 2 movesBootstrap2 movesopencv: 2 movesopencv2 moves

Skills after lidar

After lidarlidar → JavaScript: 3 observed employer moves with this skill pairlidar → React: 3 observed employer moves with this skill pairlidar → C++: 2 observed employer moves with this skill pairlidar → TypeScript: 2 observed employer moves with this skill pairlidar → ci/cd: 2 observed employer moves with this skill pairlidar → docker: 2 observed employer moves with this skill pairlidar → Node-RED: 1 observed employer moves with this skill pairlidar → python: 1 observed employer moves with this skill pairlidarJavaScript: 3 movesJavaScript3 movesReact: 3 movesReact3 movesC++: 2 movesC++2 movesTypeScript: 2 movesTypeScript2 movesci/cd: 2 movesci/cd2 movesdocker: 2 movesdocker2 movesNode-RED: 1 movesNode-RED1 movespython: 1 movespython1 moves
How to read this chart · view counts

Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.

The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.

Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.

Observed connections and move counts
ConnectionMoves
Before: python4
Before: tensorflow3
Before: C#2
Before: MYSQL2
Before: Power BI2
Before: docker2
Before: Bootstrap2
Before: opencv2
After: JavaScript3
After: React3
After: C++2
After: TypeScript2
After: ci/cd2
After: docker2
After: Node-RED1
After: python1

Roles most likely to require lidar

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Robotics Engineer1622.5%
Robotics Software Engineer2517.0%
Hardware Engineer615.0%
Tech Lead Manager29.1%
Embedded Systems Engineer25.0%
Autonomy Engineer15.0%
ML Software Engineer14.5%
Implementation Engineer24.1%
Systems Integration Engineer13.6%
Computer Vision Engineer33.3%

Roles with the most lidar postings

RolePostings mentioning skillShare of skill postings
Software Engineer7520.4%
Machine Learning Engineer328.7%
Robotics Software Engineer256.8%
Robotics Engineer164.4%
ML Engineer143.8%
Systems Engineer133.5%
Robotic Systems Engineer92.5%
Technical Program Manager71.9%
Triage Associate71.9%
Hardware Engineer61.6%

Top companies posting jobs requiring lidar

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring lidar
CompanyPostings · 90 days
Anduril Industries37
Anduril24
Waymo21
Wayve18
Applied15
Torcrobotics13
Latitude10
Applied Intuition9
CLERA9
Rivian9

Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.

Top metros hiring for lidar

NamePostingsShare
Mountain View277.4%
Sunnyvale246.5%
Santa Clara154.1%
Costa Mesa143.8%
Munich143.8%
Pittsburgh143.8%
Ann Arbor123.3%
San Francisco123.3%
Waltham102.7%

Skills commonly paired with lidar

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning lidar by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s lidar postings by all lidar postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). Adjusted posting share: 0.2% to 0.2%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,595 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.

source
Skillenai jobs index, deduplicated daily
entity_id
41e101aaff1b8331
data_as_of
2026-09-30
window_days
90
Hiring engineers who use lidar?

The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.

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Compiled by Jared Rand · Data sourced from the Skillenai labor market index