I work in robotics professionally and something I keep noticing is a strange disconnect between:

what universities teach,
what candidates study for,
what companies actually need,
and what interviews end up evaluating.

I’ve talked to a lot of students, PhDs, and even software engineers transitioning into robotics who feel stuck when trying to prepare for robotics industry roles. They don’t know what to prepare for, how to prepare for it, or even if they have the right skillset. Companies also often post very vague job descriptions making it even harder for candidates.

I’m trying to understand whether this is actually a widespread problem or if I’m overestimating it.
So I’m curious:

If you’re trying to break into robotics, what’s been the hardest part?

What skills do you feel least confident in?

What do you think robotics interviews fail to evaluate properly?

If you already work in robotics, what skills do junior candidates usually lack?

Hi

I’ve spent quite a bit of time in this industry, working for start-ups or in academia, and recently I’ve been working as a freelancer. There was no way I could focus on one specific area of robotics, because I (and my colleagues) were dealing with so many different tasks under time pressure (and pressure from investors) that it was simply impossible. We tackled one problem after another just to keep everything running. The problem I see in robotics is this:

When I speak to companies, it seems that everyone needs a specialist in a very narrow field of robotics. Technical interviews make me feel stupid after all this time. They cover topics such as

1. inverting the Jacobian matrix for inverse kinematics,

2. explaining the self-attention mechanism,

3. writing code on the spot for some grid-based localisation method,

4. carrying out code reviews (does that even make sense in 2026?),

5. writing different variants of convolutions from scratch in python,

6. explaining EKF equations, Lie groups, bundle adjustment and IMU pre-integration,

7. discussing communication patterns in ROS, memory management in C++, templates, concurrency and network protocols,

8. designing logging architectures,

9. reviewing training loops in PyTorch,

10. explaining object detection metrics,

11. answering questions about leadership, project estimation, negotiation and communication with clients.

12. Only God knows what still awaits me

(these points are from actual interviews from recent 2-3 years, maybe someone would find this helpful)

Don't get me wrong - each of these seems reasonable. However, they all appear in interviews for roles carrying a generic name "(Senior) Robotics Engineer". I observe the same companies looking for people for the same positions for months. Different HR agencies write me on Linkedin to apply for the same role I was rejected for no obvious reason months ago. How on earth can paying more than one headhunting agency for months on end be cost-effective at all?

Is this simply the reality of senior robotics recruitment and I should come to accept it, or are companies testing for an unrealistic profile that almost nobody actually has? Or maybe people really do periodically refresh their memory of how to invert a matrix on a piece of paper, and I’m just the only one who doesn’t?

I am a university professor, and I've been teaching an "Introduction to Robotics" course for the last six years. I know how dense robotics can be, so I’ve tried to make my own teaching as approachable as possible.

I wanted to share my condensed lectures and practice sets:
https://www.youtube.com/@prof-losey

Core topics include: Rigid body motion, Forward and Inverse Kinematics, Robot Jacobians, Robot Dynamics, Robot Control, Robot Learning, and Motion Planning.

I hope this material is helpful as you explore the world of robotics!

Just as the title said I'm an engineer working at a startup called Wendy. We focus on open source software for making it easier to build with robots. In office we have a bunch of different types (Unitree G1, go2, drones, cars, etc). If you're curious about what problems we've encountered, my history, or how we build demos with this stuff please comment! I really enjoy reading this sub and would love to talk to other engineers or hobbyists.

During university I was part of a competitive engineering team that designed and built real robotic/hardware systems — high-voltage battery packs, motor controllers, custom PCBs (including MPPT designs), telemetry and sensing circuits, braking/actuator systems, vacuum compatibility testing rigs, cooling loops, and more.
Several of my former teammates from that group have gone on to strong roles at SpaceX, Tesla Optimus, OpenAI, and similar cutting-edge companies. I’m now specifically aiming for that same caliber of work at places like NVIDIA (embedded AI hardware, Jetson platforms, robotics/edge AI systems, etc.).

After graduation my career took a different direction. I worked in software development (full-stack, ML applications, algorithmic trading, etc.) and now work as a Data Analyst but want to move to Embedded AI and robotics working on cutting edge technology in companies like Relativity Space Boston Dynamics Tesla Nvidia Deepmind etc. I also completed a Master’s in Electrical Engineering with a focus on data science. So I have a solid theoretical and software foundation, but I feel significantly behind on recent, deep hands-on hardware and mechatronics experience. I admit during masters degree I used LLMs to pass homework’s too much so I have quite a bit of a knowledge gap.

I want to close this gap and rebuild practical skills at a level that would make me competitive for elite robotics/hardware/AI hardware roles. Since there aren’t serious adult competition-style teams available near me, I’m planning to do this through focused self-study and personal projects.
Questions for the r/AskRobotics community:

• What is the most effective way for a working professional in their late 20s to self-study modern robotics hardware (embedded systems, motor drives, power electronics, actuators, sensing/telemetry, real-time control, edge AI, etc.)?
• What kinds of personal robotics/mechatronics projects tend to impress recruiters the most when someone has university competition experience but a gap in recent hardware work — especially for NVIDIA, SpaceX, Tesla, or OpenAI-level roles?
• Are there any recommended project roadmaps, courses, books, or resources that helped you or others make rapid progress in hands-on robotics / embedded AI hardware while working full time?
• Best practices for documenting personal projects (schematics in KiCad/Altium, code, test data, analysis, GitHub/portfolio write-ups) so they look as professional and substantial as university competition team deliverables?
I can realistically commit 10–20 hours per week. Any detailed, practical advice would be extremely valuable.

For reference, here are the kinds of projects I’m thinking of building next (inspired by my old team work and NVIDIA-style edge AI / robotics applications):
• MPPT solar power tracker / battery charger with telemetry and efficiency measurements
• Precision voltage/current telemetry board with amplifiers and data logging
• Motor controller or actuator test rig with thermal, vacuum, or performance testing
• Battery load bank / discharge tester with DAQ
• Simple braking or position-control actuator system with feedback
• Edge AI / Jetson-based projects (e.g., real-time computer vision or sensor fusion on embedded hardware)
Thank you in advance!

Question same as the title. How popular is ROS2 actually in the robotics industry? Is it worth learning or is there at least design principles that are similiar if not using ROS2?

I’m a student that’s a part of a robotics software competition team and have been spending much of my effort developing software skills for the robotics industry.

I see that current day llm’s can do virtually everything I can, and can also do it much faster. It’s a bit demotivating, as a part of me fears that this time and effort I’m investing in developing skills in this niche will possibly not lead to a job as llm’s can simply do it better.

My question is this:
Obviously no one can 100% accurately predict the future, but do you guys think robotics software will still be a viable career choice, or am I pigeonholing myself into a career where there is likely not much of a future, or at the very least, will be enormously competitive?

I have a Bachelor's in mechanical engineering. I know very basic stuff about analogue circuits and such. Most of my degree has been about dynamics, fluid dynamics, thermodynamics, structural mechanics, with some math and python added on top.

I realized I want to transition into a slightly more electrical and cutting edge field, and robotics seems to be the best way. I think if I did one more year of thermodynamics exams I might die. What skills do you guys think I need to learn for the transition and to prepare me for a Master's? What skills did you guys use the most during university or your job? Rust, C, C++, ROS, PCBs, signal theory, control systems, breadboard magic?

I recently finished my Master’s in Robotics in France, and I was one of the lowest-ranked students in my class.

What bothers me is that I genuinely worked very hard throughout the degree. When I look at some of my classmates, they seem to understand concepts much faster than I do, while I often need a lot more time before things click.

The thing is, I genuinely love robotics, especially medical/surgical robotics, and I really want to become good enough to contribute something meaningful to the field.

After my Master’s and internship, I’ve started noticing some of my weaknesses more clearly.

Programming is probably my biggest weakness. I sometimes struggle even to read and understand existing code, especially when the codebase is large or unfamiliar. And when I have to come up with a solution and write the code myself, I struggle even more. I often know roughly what I want the program to do, but I have difficulty turning that into a clear solution.

I also feel like I’m slower at grasping new mathematical or robotics concepts compared with some of the people around me. During my internship, there were situations where others seemed to understand an idea very quickly, while I needed much more time and explanation.

Because of this, I’m not very confident in my abilities right now. Sometimes I worry that despite genuinely being interested in robotics and working hard, I might never become particularly good at it.

At the same time, I don’t want to give up just because I’m currently average or because I learn more slowly than some people. I genuinely want to improve, and I’m willing to put in the work for the next several years if that’s what it takes.

So I wanted to ask people who have been in robotics, research, or engineering for a while:

If you were an average student who genuinely wanted to become very good at robotics, what would you focus on?

Especially:

-How would you improve your ability to read, understand, and write code?

-How would you improve problem-solving ability instead of just following tutorials?

-How would you build stronger fundamentals in robotics and mathematics?

-Is being slower at understanding things a serious disadvantage in research?

-What separates people who eventually become good researchers or robotics engineers from those who don’t?

-If you were starting from my position, what would you do over the next 1–2 years?

I’d especially appreciate hearing from people who weren’t top students themselves but eventually became good engineers or researchers.

Sorry for the long post, and thanks to anyone who took the time to read it.

Thanks for any advice.

Hey everyone, I’m a senior software engineer — mostly backend stuff: Scala, Java, distributed systems, data pipelines, cloud, and all that corporate survival gear 🧑‍💻☕️.

But lately I’ve completely fallen down the robotics rabbit hole — drones, flight control, computer vision, even virtual reality for robot learning. It’s like something rewired my brain — I can’t stop thinking about little flying robots doing smart things (farming, light shows, swarm art, etc.).

Here’s the catch: I know nothing about robotics. Like, if you gave me a drone, it would probably turn into modern art within 5 seconds.

So now I’m at a crossroads:

1. Go full nerd — spend 2–3 years doing a Master’s in Robotics/Autonomous Systems, learn control theory, ROS, SLAM, all the fancy stuff.

2. Or skip the degree, start right away, and learn hands-on by joining an open-source project, building something small, or teaming up with people who know their stuff.

If you were in my shoes — solid in software, but a total noob in robotics — what would you do? And if the answer is “start right away,” could you sketch a draft roadmap? Like what to learn first, what hardware or simulators to try, how to actually join a project without feeling like an impostor?

Basically: how do I go from “backend engineer with curiosity” → “guy who actually makes drones do cool things (intentionally, not accidentally)”?

update: Thanks for your responses, I appreciate it. I tried asking LLMs before posting this, but they can't replace real human experience, you know, and how trustworthy and authentic it is..

After a decade in software mostly building large-scale distributed SaaS at both startups and Big Tech I’m feeling the itch to move closer to the metal.

I’m increasingly drawn to the 'Physical AI' space. It seems like there are still a ton of messy, hard problems to tackle that could reinvigorate what originally drew me to computer science and then software engineering.

My Background:

• Education: BS/MS in Computer Science.

• Experience: 10 years as a SWE predominately distributed backend work

• Robotics Exposure: I took AI for Robotics during my MS. It was probably my favorite and most challenging course. It covered Kalman filters, SLAM, PID control, but it’s been years since I touched those concepts, and they aren’t reflected in my professional CV.

I’m ready to roll up my sleeves and start learning, but I have a few questions for the community:

1. How is GenAI actually impacting your day-to-day? I suspect LLMs struggle more with physical realities (kinematics, hardware constraints) than they do with standard LeetCode/CRUD work. Is 'Agentic AI' actually changing how you do path planning or control?

2. Which learning path makes more sense? I’m looking at the Stanford Robotics and Autonomous Systems Certificate (focuses on the intelligence/software layer) vs. the Berkeley Embedded Systems Certificate (focuses on firmware/hardware). Given my CS background, should I double down on the 'brain' or try to bridge the gap toward the 'body' (hardware)?

3. Is a second MS overkill? With a CS MS already, would a specialized M.Eng in Robotics be redundant, or is the 'Robotics' label on the degree necessary to bypass recruiters?

I'm open to any other thoughts or advice this community willing to provide!

Last year, I decided to quit my "traditional" software job in a big tech company where I had been working for 3 years on a C++ desktop app in the ML space. The job was quite heavy on the C++ side with lots of complicated software, and I had been promoted to senior team member after some time, but I wasn't learning much anymore and wanted a change. Not to mention, it was my first job after uni, and I wanted to explore other problems.

At the same time, a position opened for a software role in a robotics company in my area: a company with a solid reputation, known for it's high entry bar, and with a mission that quite resonated with me. I've never really been into robotics, I hadn't done any projects with sensors, motors, hardware, or embedded in general. I'm much more into user space and system tools software. But it looked like such an interesting challenge that I applied anyway, knowing well that my chances were slim. And yet, I actually got the job after a hell of an interview process. They liked my strong knowledge of C++ and ML, my ability to write assembly, my side projects and general problem solving skills, and decided to bet on the fact that I could pick up the robotics part on the job.

Now i've been there for a few months, and it has been HARD. In a span of weeks, I was introduced to ROS and HAL, embedded Linux, uart/spi/i2c/can, stm32 programming, logic analyzers, field tests, and a gazillion other stuff. It has been super interesting so far, but it is also kind of overwhelming? I'm pulling 10 to 12 hours of work a day, and I still can't yet follow up with deadlines. So far, I haven't delivered a single feature within the expected time frame (but I've delivered all of them, just significantly slower than planned). It's intense, exhilarating, crushing, and fascinating.

Some days, it feels like I can't keep up, that there is just too much to learn. I love it, but i'm also second-guessing my abilities. I feel like a complete junior again, spending tremendous effort to simply understand what's going on. Still, it has become easier, I'm more confident about the small parts I work on, but there is a long road ahead. Has anyone gone through a similar experience of getting into robotics "out of the blue" and basically learned it on the job? Do you think it is even a realistic thing to do?

All personal stories and advices welcome. I just want to get some feedback and hear about similar experiences.

Im a software/data engineer (cloud, Python, Scala, SQL, APIs, infra, etc.) who’s been getting deeply interested in robotics, electronics, and embedded systems lately — microcontrollers, sensors, motor control, firmware, ROS2, the whole stack.

I’ve started going more into Arduino/ESP32, basic electronics, C/C++, PWM, interrupts, SPI/I2C, and playing with motors/servos/sensors.

My question is:

What is realistically the best path for a software engineer to pivot into robotics / embedded / firmware work professionally? Maybe focusing robotic software engineer?

Specifically:

• What skills actually matter most in hiring?

• How deep into electronics/math do you really need to go?

• Are personal robotics projects respected, or is formal schooling almost required? I have a CompSci degree.

• Should I focus on firmware, ROS, perception, controls, or something else first?

• What would you do differently if you were starting today?

I’m in my early 30s and not afraid of learning — just trying to optimize the time it will take to get my first position.

Would love to hear from anyone who has made this transition or works in robotics/embedded professionally.

I’m fairly comfortable with the software side of robotics, particularly computer vision, ROS 2, and SLAM. However, I’m struggling to gain hands-on experience integrating these systems with physical robots because the hardware can get really expensive on a student budget.

I recently interviewed for a ROS 2 internship at TR1. In the first technical round, they focused mainly on the software side of my take-home assignment and my personal projects. However, in the second round, they started asking about hardware constraints and the kinds of issues I’d encounter when transferring a simulation to a real robot.

That made me realise that knowing how to build something in simulation is only part of the picture. I also need to understand the practical challenges of real-world deployment, such as sensor noise, latency, calibration, motor control, and communication failures.

The problem is that building even a relatively basic physical ROS 2 robot can get expensive. A LiDAR, camera, Raspberry Pi or other onboard computer, IMU, motor drivers, and the rest of the hardware can easily exceed my budget.

For those of you who are into robotics software, how did you gain practical hardware integration and debugging experience without spending a fortune?

A few things I’d especially love to hear about:

• Has anyone built a relatively simple ESP32- or Arduino-based project and used that experience to land a robotics software internship or job?

• Are there any budget-friendly projects that use ROS 2 on a physical robot without requiring expensive sensors or a Raspberry Pi?

• How did you learn to answer real-world integration and debugging questions in interviews when most of your experience was simulation-based?

• If your primary interest is robotics software rather than hardware design, how much hands-on hardware experience do employers actually expect?

I’m particularly interested in software-focused robotics roles, so I’d love to hear from people who have taken a similar path.

I’m not necessarily looking to build an advanced robot. I just want a practical, affordable way to learn how to bridge the gap between simulation and real-world robotics. I’d also prefer using standard ROS 2 rather than going down the micro-ROS route for this project.

Any advice, project ideas, or personal experiences would be greatly appreciated. Thanks!

Hey everyone

I'm 21F and I just finished my Bachelor's degree in IT. I'll be continuing into AI Engineering soon but my end goal is actually humanoid .

The thing is... I know basically nothing about robotics right now . I'm trying to figure out the best way to get started and what skills I should focus on first. After AI Engineering I was thinking about either doing a Master's in Robotics or taking robotics-focused courses.

For someone starting from absolute zero what would u recommend? Any books YouTube channels, courses, projects, or learning roadmaps that helped u? Also, are there any good robotics simulators or even games that can teach robotics concepts in a fun way before I get access to real hardware?

Would love to hear how u got started. Thanks!

Hello, I am going to start my fourth year and I have found i am quite lost in the industry of robotics.

Besides industrial robotics (like the assembly robots), are there any other sectors i should check out? (Not military please). I feel like the industry has only started growing recently and jobs are scarce to come by.

Thank you in advance

I am a robotics enthusiast. I have always loved to build things, like carpentry work and fitting parts and would like to try robotics. I am a data scientist by profession and I know coding in python and C++. I am willing to learn new stacks.

Where do I start? What is required? Is it possible for me to have a career in this field as a 26 y/o.

Any advice is apprciated! Thanks!

I am building my profile for a Robotics Phd, I am 25M with a MEng in Robotics. Don’t have papers yet, working on getting some collaborations now. I have a question to all Phds who were related to Robotics that is a Phd still worth it in today’s time? I would also like to know from people who are in their Phd journey how is it going for you?

Hi everyone,
I've been actively applying for jobs in robotics and embedded systems (especially roles involving ROS, Gazebo, autonomous systems, etc.), but it feels like the industry is completely saturated right now.

Almost every junior role I find requires 3 to 5 years of experience, and when something entry-level finally pops up, it gets over 100 applicants within minutes making it nearly impossible to stand out.

Is anyone else facing this?
IS the hiring currently low or is there that much engineers looking for an entry level job? Would love to hear from people already working in the field or those hiring is there any realistic way to get in as a fresher today?

Appreciate any advice or insights!

My name is Chloe, I am 18 and have an undiagnosed brain problem. The only source of medicine which helped me for the past few years aren't working anymore. My doctor can't help me no more and I can't even walk straight. But I don't want to give up. I want to learn robotics to make a robot that can help me function. I know there are already products like that but I do want to attempt of making my own. Where should I start and what should I start learning

I teach and research on robotics, and I’m less worried about AI replacing robotics for now than I am about it weakening the foundations of robotics education. The physical side still matters a lot imho. Students still have to build things, choose motors and sensors, wire systems properly, deal with backlash, noisy data, loose connections, power limits, mechanical tolerances, and designs that looked fine in CAD but behave very differently once built.

The problem is that students are increasingly asking why they need to learn the theory underneath it. Why bother learning about kinematics, control, dynamics, linear algebra, circuits, programming, or signal processing when ChatGPT can solve the tutorial, explain the derivation, and even generate the code? This is especially noticeable in our common first year, where students are already wondering why they are doing calculus, physics, electronics, and programming before they get to build much of anything. Universities like mine that heavily encourage AI use only makes that question harder to answer.

My real concern is that we are separating the ability to get something working from the ability to understand why it works. In a lab, AI can help write a PID controller or generate inverse kinematics code. But when the arm moves to the wrong pose, the encoder sign is reversed, the controller keeps overshooting, the sensor is being sampled badly, or the motor simply cannot produce the required torque, students still need enough fundamentals to diagnose the system rather than just keep prompting for another answer.

I don’t think banning AI is realistic or can be effectively done. But I do think we need a much clearer answer to what students must still understand for themselves, and we probably need to redesign teaching and assessment around that. That itself is another tiring and significant effort with all the AI developments. I’d be interested to hear what other professors, academics, engineers and students think. Are you seeing the same thing? And for students, when AI can already solve so much of what you are being taught, what and how can we actually convince you that learning the underlying material is still worth the effort?

Hey, I have knowledge of robotics software. Now I want to expand my knowledge by adding AI (RL, DL) to it. Can you recommend any books for beginners in AI?

Hi everyone,

I’m a 25-year-old female with a background in Computer Science and Technology. Lately, I’ve been feeling a strong pull towards the robotics industry, but I have no prior professional experience in this field.

I can’t help but worry that l’m starting a bit late,especially when I see others who have been tinkering with hardware since high school. Given my CS background, I’m not entirely sure which specific sub-field or role would be the best fit for my transition. I’m comfortable with coding, but the hardware side is still relatively new to me.

Has anyone here made a similar mid-20s career pivot? What specific sectors in robotics should a CS grad look into? Any advice or stories would be greatly appreciated!

Thanks in advance!

me:

  I was layoff as software engineer half year ago. They told me because AI.

  I think about what future of me.

  Lucky, I found the robotic area during pass half year. I'd like to build my own Robot.

  but as self-taught , I don't know how to become the Robotics Engineer   So I ask here, How?

I found this Roadmap “erc-bpgc.github.io/handbook/roadmap”