SLAM jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-11-06, SLAM appears in 219 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning SLAM, with demand share up 0.9% vs the prior 4 weeks.
Last updated · 90d ending 2026-11-06
Which roles want SLAM?
Upload your resume and Skillenai will show which roles your SLAM experience fits, which skills you already cover, and what is missing.
Frequently asked questions about SLAM
+Is SLAM in demand in 2026?
Yes. SLAM appears in 219 job postings indexed by Skillenai over the 90 days ending 2026-11-06. Software Engineer accounts for the most postings mentioning SLAM (19.6% of all postings mentioning SLAM).
+What jobs require SLAM?
According to the Skillenai jobs index over the 90 days ending 2026-11-06, among roles with at least 20 postings, the highest shares mentioning SLAM are Perception Engineer (24.1% of that role’s postings mention SLAM), Computer Vision Engineer (23.5% of that role’s postings mention SLAM), Robotics Engineer (18.6% of that role’s postings mention SLAM).
+What skills are commonly paired with SLAM?
Across job postings indexed by Skillenai (90 days ending 2026-11-06), SLAM most often appears alongside Python, C++, sensor fusion, Computer Vision, PyTorch.
+Where is SLAM most in demand?
As of 2026-11-06, the metro areas posting the most jobs requiring SLAM are Sunnyvale, San Francisco, Costa Mesa, London, Austin, according to the Skillenai jobs index.
+How can I keep up with new SLAM content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning SLAM alongside the jobs index. You can subscribe to a daily email digest of new SLAM content from your Skillenai account.
+Which skills come before and after SLAM?
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 SLAM — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around SLAM
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before SLAM
Skills after SLAM
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.
| Connection | Moves |
|---|---|
| Before: python | 2 |
| Before: footer | 1 |
| Before: ISO 26262 | 1 |
| Before: Lab and Test Engineering | 1 |
| Before: simulation | 1 |
| Before: Multithreading | 1 |
| Before: multibody dynamics | 1 |
| Before: Calendar component | 1 |
| After: machine learning | 2 |
| After: embedded systems | 1 |
| After: neural networks for object detection | 1 |
| After: Wireless Sensor Network | 1 |
| After: sql | 1 |
| After: computer vision | 1 |
| After: Sensor Algorithms Development | 1 |
| After: kubernetes | 1 |
Roles most likely to require SLAM
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Perception Engineer | 7 | 24.1% |
| Computer Vision Engineer | 24 | 23.5% |
| Robotics Engineer | 18 | 18.6% |
| Robotics Software Engineer | 16 | 10.4% |
| Deep Learning Engineer | 3 | 8.3% |
| Autonomy Engineer | 2 | 5.6% |
| AI Infrastructure Engineer | 3 | 4.3% |
| AI Research Scientist | 3 | 3.8% |
| AI Research Intern | 1 | 3.1% |
| AI Product Engineer | 2 | 2.5% |
Roles with the most SLAM postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 43 | 19.6% |
| Computer Vision Engineer | 24 | 11.0% |
| Robotics Engineer | 18 | 8.2% |
| Robotics Software Engineer | 16 | 7.3% |
| Research Scientist | 13 | 5.9% |
| ML Engineer | 11 | 5.0% |
| Machine Learning Engineer | 8 | 3.7% |
| Research Engineer | 8 | 3.7% |
| Perception Engineer | 7 | 3.2% |
| AI Infrastructure Engineer | 3 | 1.4% |
Top companies posting jobs requiring SLAM
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Anduril Industries | 21 |
| Wayve | 16 |
| CLERA | 13 |
| General Motors | 7 |
| Renesas | 6 |
| Snap | 6 |
| Quadient | 5 |
| Applied Intuition | 5 |
| Torcrobotics | 4 |
| Symbotic | 4 |
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 SLAM
| Name | Postings | Share |
|---|---|---|
| Sunnyvale | 19 | 8.7% |
| San Francisco | 18 | 8.2% |
| Costa Mesa | 8 | 3.7% |
| London | 6 | 2.7% |
| Austin | 5 | 2.3% |
| Seattle | 5 | 2.3% |
| Columbia | 4 | 1.8% |
| Munich | 4 | 1.8% |
| Needham | 4 | 1.8% |
Skills commonly paired with SLAM
Explore related pages
How this was computed
Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-11-06. 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 SLAM by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s SLAM postings by all SLAM 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: 0.1% to 0.1%. 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 2,471 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-07-07 to 2026-10-05 and 2026-08-04 to 2026-11-02 (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
- a7aee89fd4bfd6b4
- data_as_of
- 2026-11-06
- window_days
- 90