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

As of 2026-09-30, imitation learning appears in 235 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning imitation learning, with demand share down 9.1% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
235
Demand vs prior month
down 9.1% vs the prior 4 weeks
Top role · 12.3% of skill postings
Top hiring metro
Sunnyvale

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Frequently asked questions about imitation learning

+Is imitation learning in demand in 2026?

Yes. imitation learning appears in 235 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Machine Learning Engineer accounts for the most postings mentioning imitation learning (12.3% of all postings mentioning imitation learning).

+What jobs require imitation learning?

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 imitation learning are Robotics Engineer (12.7% of that role’s postings mention imitation learning), AI Engineering Lead (8.8% of that role’s postings mention imitation learning), AI Research Intern (8.3% of that role’s postings mention imitation learning).

+What skills are commonly paired with imitation learning?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), imitation learning most often appears alongside Reinforcement learning, Python, PyTorch, C++, MuJoCo.

+Where is imitation learning most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring imitation learning are Sunnyvale, San Francisco, Munich, Mountain View, Santa Clara, according to the Skillenai jobs index.

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

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

+Which skills come before and after imitation learning?

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 imitation learning — last 90 days

Salary distribution

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

Career paths around imitation learning

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before imitation learning

Before imitation learningregularization → imitation learning: 1 observed employer moves with this skill pairworkplace connection → imitation learning: 1 observed employer moves with this skill pairintra-company lunch app → imitation learning: 1 observed employer moves with this skill pairLLMs → imitation learning: 1 observed employer moves with this skill pairBERT → imitation learning: 1 observed employer moves with this skill pairfinetuning → imitation learning: 1 observed employer moves with this skill pairRoBERTa → imitation learning: 1 observed employer moves with this skill pairrobotics and automation → imitation learning: 1 observed employer moves with this skill pairimitationlearningregularization: 1 movesregularization1 movesworkplace connection: 1 movesworkplaceconnection1 movesintra-company lunch app: 1 movesintra-companylunch app1 movesLLMs: 1 movesLLMs1 movesBERT: 1 movesBERT1 movesfinetuning: 1 movesfinetuning1 movesRoBERTa: 1 movesRoBERTa1 movesrobotics and automation: 1 movesrobotics andautomation1 moves

Skills after imitation learning

After imitation learningimitation learning → RAG pipeline: 1 observed employer moves with this skill pairimitation learning → ROS2: 1 observed employer moves with this skill pairimitation learning → IsaacSim: 1 observed employer moves with this skill pairimitation learning → chatbot: 1 observed employer moves with this skill pairimitation learning → dataset curator: 1 observed employer moves with this skill pairimitation learning → AI agents: 1 observed employer moves with this skill pairimitation learning → large language models: 1 observed employer moves with this skill pairimitation learning → planning algorithms: 1 observed employer moves with this skill pairimitationlearningRAG pipeline: 1 movesRAG pipeline1 movesROS2: 1 movesROS21 movesIsaacSim: 1 movesIsaacSim1 moveschatbot: 1 moveschatbot1 movesdataset curator: 1 movesdataset curator1 movesAI agents: 1 movesAI agents1 moveslarge language models: 1 moveslarge languagemodels1 movesplanning algorithms: 1 movesplanningalgorithms1 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: regularization1
Before: workplace connection1
Before: intra-company lunch app1
Before: LLMs1
Before: BERT1
Before: finetuning1
Before: RoBERTa1
Before: robotics and automation1
After: RAG pipeline1
After: ROS21
After: IsaacSim1
After: chatbot1
After: dataset curator1
After: AI agents1
After: large language models1
After: planning algorithms1

Roles most likely to require imitation learning

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

RolePostings mentioning skill% of role postings mentioning skill
Robotics Engineer912.7%
AI Engineering Lead38.8%
AI Research Intern28.3%
Technical Lead Manager26.9%
Postdoctoral Researcher14.8%
Lecturer14.3%
Robotics Software Engineer64.1%
Researcher23.2%
Deep Learning Engineer13.0%
Research Scientist252.9%

Roles with the most imitation learning postings

RolePostings mentioning skillShare of skill postings
Machine Learning Engineer2912.3%
Research Scientist2510.6%
ML Engineer208.5%
Robot Learning Engineer146.0%
Software Engineer135.5%
Research Engineer93.8%
Robotics Engineer93.8%
AI Engineering Team Lead62.6%
Robotics Software Engineer62.6%
AI Engineer52.1%

Top companies posting jobs requiring imitation learning

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

Top companies posting jobs requiring imitation learning
CompanyPostings · 90 days
Wayve24
CLERA22
Neura Robotics20
Scale AI9
Bosch7
General Motors6
NVIDIA6
Apptronik6
Torcrobotics5
Generalrobotics5

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 imitation learning

NamePostingsShare
Sunnyvale3113.2%
San Francisco2711.5%
Munich146.0%
Mountain View125.1%
Santa Clara104.3%
Aachen73.0%
Singapore73.0%
Metzingen62.6%
Shanghai62.6%

Skills commonly paired with imitation learning

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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 imitation learning by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s imitation learning postings by all imitation learning 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 2,595 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
905e2d62f93fb1ed
data_as_of
2026-09-30
window_days
90
Hiring engineers who use imitation learning?

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