Robotics Programming Languages: What 2,724 Job Postings Reveal

James Dam •

13 min read • Last updated January 16, 2026

Every robotics guide ranks programming languages from #1 to #10. But our analysis of 2,724 active robotics job postings (as of early Jan 2026) reveals a different story: Python and C++ rarely exist in isolation.

Of the 907 jobs mentioning Python, 68% also mention C++. Of the 756 jobs mentioning C++, 82% also list Python. Rather than competing, these languages coexist in the same technical ecosystems, often within the same job descriptions.

The real question isn’t “Python vs C++?” It’s “Which should I learn first for my robotics career path?”

Here’s what the data shows for top software robotics roles:

Your target role determines your language priorities. Let’s break down why both languages dominate, where each matters most, and what you should learn first.

Table of Contents

The Two-Language Reality: Why Robots Need Both

Robots face what the industry calls the “Two-Language Problem.” They need to do two fundamentally different things simultaneously:

1. Act fast — Move motors and read sensors in microseconds
2. Think smart — Process images, plan paths, and run neural networks

Think of it like a human body: C/C++ is the nervous system and muscles. Python is the conscious brain.

C/C++: Real-Time Control and Hardware

C and C++ handle the “hard” real-time requirements where milliseconds matter.

Why robotics teams use C/C++:

Speed is critical. C++ compiles directly to machine code and runs fast enough for control loops. When a humanoid robot needs to balance on two legs, a 5-millisecond delay can cause it to fall over. Python’s interpreted nature makes it too slow for these tight control loops.

Direct hardware access. Manufacturers of LiDARs, cameras, and motor controllers write their drivers in C/C++. If you’re interfacing with sensors or actuators at a low level, you’re working in C/C++.

Memory control. Manual memory management prevents garbage collection pauses that would be fatal in real-time systems. When controlling a robot arm moving at high speed, you cannot afford unpredictable pauses.

Typical C/C++ tasks in robotics:

• Motor control loops running at 1kHz+
• SLAM (Simultaneous Localization and Mapping) algorithms
• Sensor fusion and filtering
• Computer vision preprocessing
• Real-time path execution

Python: High-Level Logic and AI

Python handles the “soft” cognitive tasks where development speed and flexibility matter more than raw performance.

Why robotics teams use Python:

Development speed. You can prototype a Python script in 10 minutes that would take hours in C++. This “fail fast” approach is essential for research and iterative development.

AI ecosystem dominance. PyTorch, TensorFlow, scikit-learn, and virtually every modern machine learning framework is Python-first. If you’re doing anything with neural networks or machine learning, you’re using Python.

Glue code and orchestration. Python excels at connecting different systems—taking data from C++ modules, sending it to databases, exposing it via web APIs, or coordinating high-level mission logic.

Typical Python tasks in robotics:

• Training and running neural networks
• High-level path planning strategies
• Mission orchestration (“go to kitchen, pick up object, return”)
• Data analysis and visualization
• Automated testing and simulation scripting

How They Work Together: ROS

In ROS (Robot Operating System)—the industry standard middleware—teams commonly write performance-critical nodes (like LiDAR processing or motion control) in C++, then coordinate the robot’s high-level behavior using Python scripts.

At companies like Boston Dynamics (91.7% C++, 75% Python) or NVIDIA (86.7% C++, 83.3% Python), both languages work together in the same systems.

Important caveat: When job postings mention multiple languages, they often list them as alternatives (e.g., “Experience with C, C++, or Python”). These percentages indicate which languages exist in each technical ecosystem, not strict requirements for every hire.

By Career Path: Which Language Matters More

Your target role determines whether you should prioritize Python or C++. Here’s what the data reveals across different robotics specializations:

Software & AI-Focused Roles

Machine Learning Engineer (246 jobs analyzed)

• Python: 93.5% of postings
• C++: 76.0% of postings
• C: 18.3% of postings

Guidance: Python is primary. Most ML engineering work happens in Python (PyTorch, TensorFlow), with C++ used for deploying models to production or optimizing inference pipelines. If you’re focused on training models and developing AI algorithms, start with Python.

Research Scientist (173 jobs analyzed)

• Python: 94.8% of postings
• C++: 56.6% of postings
• MATLAB: 12.1% of postings

Guidance: Python dominates research roles. C++ appears in about half of postings but is often listed as “nice to have” rather than required. Academic and research positions prioritize rapid experimentation over production optimization.

Control & Motion-Focused Roles

Motion Planning Engineer (90 jobs analyzed)

• C++: 87.8% of postings
• Python: 78.9% of postings
• C: 18.9% of postings

Guidance: C++ leads here. Motion planning algorithms need to run in real-time, and most production motion planning libraries (OMPL, MoveIt) are C++-based. Python is common for testing, prototyping, and tooling, but C++ is the primary language.

Robotics Software Engineer (203 jobs analyzed)

• C++: 84.2% of postings
• Python: 82.3% of postings
• Rust: 14.8% of postings

Guidance: Nearly equal split, slight C++ preference. This is the most “full-stack” robotics role, requiring comfort in both languages. Companies like Shield AI (100% C++, 84.6% Python) expect engineers to work across the entire stack.

Hardware & Embedded Roles

Embedded Systems Engineer (141 jobs analyzed)

• C++: 80.9% of postings
• C: 73.0% of postings
• Python: 61.7% of postings

Guidance: C and C++ are essential. When working close to hardware—programming microcontrollers, writing device drivers, or optimizing for resource-constrained systems—C/C++ are the tools of the trade. Python appears in these roles primarily for build scripts, testing, and PC-side tooling.

Controls Engineer (108 jobs with software language data analyzed)

• Python: 58.3% of postings
• C++: 44.4% of postings
• C: 19.4% of postings

Guidance: Controls engineering roles vary widely. Some focus on software-based control algorithms (state estimation, modern control theory) and use Python/C++. Others focus on industrial automation and require PLC programming instead. Check job descriptions carefully to understand which type of controls role you’re looking at.

Other Languages: Where They Fit

While Python and C++ dominate (appearing in 78% and 65% of software robotics jobs respectively), several other languages serve specific niches.

MATLAB: Academic and Control Theory

Frequency: 124 jobs (5% of all robotics jobs)

MATLAB remains common in academia and R&D for designing control systems and running simulations. However, even in research-heavy roles, Python has largely displaced it: 94.8% of Research Scientist postings mention Python versus only 12.1% mentioning MATLAB.

When MATLAB matters:

• Control system design and simulation
• Aerospace and defense R&D (26.5% of aerospace jobs mention it)
• Mathematical modeling of complex systems

Engineers typically use MATLAB for prototyping mathematical models, then rewrite the algorithms in C++ for production deployment.

Rust: The Safety-First Challenger

Frequency: 59 jobs (2% of all robotics jobs) Median salary: $192,000 (highest, but small sample size)

Rust offers C++-level performance with guaranteed memory safety—a compelling value proposition for safety-critical robotics systems.

Notable adopter: Anduril Industries lists Rust in 45% of their robotics postings, signaling their commitment to cutting-edge tooling for autonomous defense systems.

Watch this space: Linux kernel and ROS 2 are both actively integrating Rust support. While still niche today, adoption is growing in autonomous vehicles and surgical robotics where safety is paramount.

Java: Enterprise and Legacy Systems

Frequency: 70 jobs (3% of all robotics jobs)

Java appears primarily in enterprise contexts and older industrial systems. Amazon’s robotics division is an outlier, with 66.7% of their postings mentioning Java—likely reflecting their broader infrastructure and cloud services integration.

When Java matters:

• Android-based robotics applications
• Enterprise robotics systems with Java-heavy infrastructure
• Some legacy industrial robot controllers

C#: Simulation and Windows Industrial

Frequency: 53 jobs (2% of all robotics jobs)

C# serves two main niches: Unity-based robot simulation and Windows-based industrial control systems.

When C# matters:

• Building Digital Twins in Unity
• Windows IoT industrial applications
• Robot simulation and visualization

JavaScript/TypeScript: Web Interfaces

Frequency: 33 jobs (1% of all robotics jobs)

You don’t program the robot in JavaScript—you program the remote control interface. Modern robotics systems need dashboards, monitoring tools, and operator interfaces, which are increasingly web-based.

When it matters:

• Robot fleet management dashboards
• Remote operation interfaces
• Data visualization tools (like Foxglove)

Does Language Choice Affect Salary?

Common career advice suggests “Learn C++ because it pays more.” Let’s see what the data actually shows.

Among the 475 robotics jobs with posted salary ranges:

C++ shows a $5,000 higher median salary than Python—a 3% difference.

This is statistical noise, not a meaningful pay premium. Four factors actually drive your salary:

1. Role type — Motion Planning Engineers and ML Engineers have different compensation bands regardless of language
2. Seniority — Entry-level ($120k median) vs Senior ($185k median) matters far more than Python vs C++
3. Company — FAANG vs manufacturing SMB can be a 2x difference
4. Location — San Francisco vs Midwest can be a 50%+ difference

What about Rust’s $192k median? With only 38 salary data points, this likely reflects the types of companies adopting Rust (Anduril, autonomous vehicle startups, cutting-edge defense contractors) rather than a language premium. These companies pay well regardless of tech stack.

Actionable takeaway: Choose your language based on target role and career interests, not compensation optimization. The language choice is a rounding error compared to other salary factors.

Explore our robotics salary guide to understand compensation by role and seniority.

Learning Path Recommendations

What should you actually learn? Here’s guidance based on different starting points and career goals:

Starting from Zero

If you’re interested in AI, machine learning, or research: Start with Python. The AI ecosystem is Python-first, and you’ll be productive faster. Learn the basics of programming, data structures, and algorithms in Python before considering C++.

If you’re interested in embedded systems or hardware: Start with C++ (or C for microcontrollers). Get an Arduino or STM32 development board and work through tutorials. Understanding how code interacts with hardware is fundamental to these roles.

If you’re interested in industrial automation and factory robotics: Check job descriptions carefully—many industrial roles require PLC programming (Ladder Logic, Structured Text) rather than traditional software languages. This is a distinct skill path from Python/C++ software development.

Many software robotics careers will eventually benefit from familiarity with both Python and C++, but that doesn’t mean you need to learn them simultaneously. Master one first, then expand.

If You Know Python, Should You Add C++?

Consider C++ if targeting:

• Motion Planning Engineer roles (87.8% mention C++)
• Robotics Software Engineer roles (84.2% mention C++)
• Any role involving real-time systems or embedded hardware

You can likely defer C++ if targeting:

• Machine Learning Engineer roles focused on model development
• Research Scientist positions in AI/ML
• Robotics roles specifically focused on high-level planning and decision-making

The data shows 68% of Python jobs also mention C++, but remember these are often listed as alternatives, not strict requirements.

If You Know C++, Should You Add Python?

Consider Python if targeting:

• Any role involving machine learning or neural networks
• Research positions
• Roles emphasizing rapid prototyping and experimentation

You can likely defer Python if targeting:

• Pure embedded systems development
• Real-time control systems engineering
• Hardware-focused engineering roles

The data shows 82% of C++ jobs also mention Python, but for embedded systems roles, Python often appears as “nice to have” for tooling rather than core development work.

Role-Specific Quick Reference

Company Culture Signals

Programming language preferences reveal company technical culture and priorities. If you have strong language preferences, you can use this to guide your job search:

Python-Heavy Companies (AI/Simulation Focus)

Signal: These companies emphasize AI research, simulation, and rapid development cycles. Strong Python skills will carry you far.

C++-Heavy Companies (Real-Time Control)

Signal: Performance-critical, hardware-intensive systems where real-time control and production-grade software are essential. Deep C++ expertise is valued.

Enterprise/Infrastructure

Amazon Robotics: 90.9% Python, 81.8% C++, 66.7% Java

Signal: Diverse technology stack reflecting enterprise infrastructure needs. Java’s high presence is unusual for robotics but makes sense given Amazon’s broader tech ecosystem.

Emerging Tech Adopters

Anduril Industries: 85% C++, 80% Python, 45% Rust

Signal: Cutting-edge defense technology company willing to adopt modern languages like Rust for safety-critical autonomous systems.

The Verdict

Python and C++ aren’t competitors in software robotics—they’re complementary tools that coexist in the same technical ecosystems. The data from 2,724 active job postings shows both languages appearing together far more often than in isolation.

Key takeaways:

1. Choose based on your target role. Motion Planning Engineers need C++ more than Python. ML Engineers need Python more than C++. Robotics Software Engineers benefit from both.

2. Don’t optimize for salary. The $5,000 median difference (3%) between C++ and Python is noise compared to role, seniority, company, and location factors.

3. Plan for depth, not breadth. Master one language first rather than learning both superficially. Robotics engineering requires deep expertise, not checkbox knowledge.

4. Consider the industrial automation path separately. If you’re interested in factory automation and traditional controls engineering, PLC programming may be more relevant than Python/C++. Check actual job requirements.

5. Use company language patterns to guide your job search. If you strongly prefer Python, target companies like GM and Toyota Research. If you prefer C++, target companies like Boston Dynamics and Shield AI.

Next steps:

• Browse active robotics jobs by your preferred language to see what companies are hiring
• Explore our robotics salary guide to understand compensation by role and seniority
• Review specific role pages to understand the full skill requirements beyond just programming languages

About this analysis: Data extracted from 2,724 active robotics job postings across 18 role types, 20+ industries, and 50+ countries. Salary data represents 475 jobs with posted compensation ranges (17.4% of dataset).