Engineering and Science Career Paths

Over the last few years, we’ve seen the rise of distinct AI roles: Some focus on building models. Some specialize in prompting them. Some orchestrate entire multi-agent ecosystems. But here’s the challenge: Most people dive into AI without a clear path. They juggle multiple tutorials, frameworks, and buzzwords — without direction. And often feel stuck… despite all the learning. That’s why I created this visual roadmap to demystify what it actually takes to build a successful career in AI—whether you’re starting out, switching domains, or upskilling. 𝟰 𝗥𝗼𝗮𝗱𝗺𝗮𝗽𝘀. 𝟰 𝗖𝗮𝗿𝗲𝗲𝗿 𝗣𝗮𝘁𝗵𝘀. 𝟭 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 𝗩𝗶𝘀𝗶𝗼𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Master LangChain, LangGraph, AutoGen, CrewAI Design decision-making agents with memory, context, and orchestration Build truly autonomous multi-agent systems that reason, act, and collaborate 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Learn the foundations of GenAI: transformers, LLMs, embeddings Build applications using OpenAI, Hugging Face, Cohere, and Anthropic Fine-tune models, use vector databases (RAG), and bring GenAI apps to life 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Go deep into math, stats, algorithms, feature engineering, and modeling Master Python, Scikit-Learn, XGBoost, and model deployment Build solid ML portfolios that showcase real-world impact 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 (𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗔𝗜) Cover it all: computer vision, NLP, reinforcement learning, AI ethics, model governance Use TensorFlow, PyTorch, and integrate AI into products end-to-end Prepares you for both research-driven and production-focused roles What’s unique about this roadmap? Clear step-by-step milestones Specific tooling and frameworks to focus on Career-aligned structure based on real job roles End-to-end guidance from fundamentals to job search Who is this for? College students entering AI Professionals switching to ML or GenAI roles Engineers looking for clarity in a noisy landscape AI educators mentoring the next wave of practitioners Startups guiding their technical talent in AI-first environments This is the kind of map I wish I had when I started. If this helps you or someone in your network: Repost it to reach more learners

“I love being a scientist. What if I go work in industry and never feel that way again?” This is one of the questions I begin my 𝗛𝗼𝘄 𝘁𝗼 𝗟𝗮𝗻𝗱 𝗬𝗼𝘂𝗿 𝗗𝗿𝗲𝗮𝗺 𝗝𝗼𝗯 𝗥𝗶𝗴𝗵𝘁 𝗢𝘂𝘁 𝗼𝗳 𝗚𝗿𝗮𝗱 𝗦𝗰𝗵𝗼𝗼𝗹 workshops with. It’s one of many questions I’ve been asked by early-career scientists – questions about worries and fears that rarely get asked out loud in a group. Questions that don’t come out in a career discussion. They are unspoken, but very real and very powerful. A variant that I often hear is: “𝘐𝘧 𝘐 𝘨𝘰 𝘸𝘰𝘳𝘬 𝘪𝘯 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘺, 𝘸𝘪𝘭𝘭 𝘐 𝘳𝘦𝘨𝘳𝘦𝘵 𝘯𝘰𝘵 𝘣𝘦𝘪𝘯𝘨 𝘢 𝘴𝘤𝘪𝘦𝘯𝘵𝘪𝘴𝘵 𝘢𝘯𝘺 𝘮𝘰𝘳𝘦?” I actually feel a bit excited when I’m asked this question, because I get to say: “𝘕𝘰, 𝘺𝘰𝘶 𝘸𝘰𝘯’𝘵 𝘳𝘦𝘨𝘳𝘦𝘵 𝘪𝘵 𝘢𝘵 𝘢𝘭𝘭. 𝘉𝘦𝘤𝘢𝘶𝘴𝘦 𝘺𝘰𝘶 𝘸𝘪𝘭𝘭 𝘴𝘵𝘪𝘭𝘭 𝘣𝘦 𝘢 𝘴𝘤𝘪𝘦𝘯𝘵𝘪𝘴𝘵.” Being a scientist isn’t about the work you do. It’s about 𝘩𝘰𝘸 𝘺𝘰𝘶 𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩 the work you do. It’s about using the skills you’ve learned from your science training.  Skills like: 📍A systematic approach to solving problems 📍Critical analysis and abstract thinking 📍The ability to learn anything on your own 📍Persistence in the face of problem after problem after problem… It’s about bringing the attributes of a scientist to your work – those strengths you’ve always had that likely led you to become a scientist in the first place.  Attributes like: 📍Curiosity about why things work the way they do 📍Excitement about discovery and exploring the unknown 📍Skepticism and a habit of questioning assumptions 📍Integrity and a drive to uncover the truth You will take these skills and attributes with you into any career path you follow. They will provide you with a unique value proposition for your prospective employer. Your coworkers will know what it means to be a scientist when they see how you think and act and solve problems and make a difference. And when you get a few years into your industry career and see that you didn’t leave anything behind, but instead found a powerful new way to be a scientist… ...you won’t regret a damned thing. 🙌 🚀 Do you agree? Disagree? Let us know. 👇 Also: Any scientist skills or attributes that I missed? _______________________ I've led 200+ workshops in 60+ institutions across 4 continents helping more than 2500 PhD scientists understand and embrace the #IndustryMindset. It's the work I'm most passionate about at TurningScience. #PhDEmployability #industryscientist

📢 Professor's responsibility: Preparing students for industry roles (responding to recent post by Andrew Akbashev) In my role as a faculty member, I’m dedicated to preparing students and postdocs primarily for impactful careers in industry. The reasons for this are: - Job Market Reality: Most opportunities lie in industry, demanding we equip our learners with necessary skills. - Work-Life Balance: Industry often offers better balance and compensation, aspects crucial for our students' awareness. - Making an Impact: It's in industry where one can often see the direct application and impact of their research. My approach to this includes: - Early Exposure: Introducing students to the variety of roles available in industry from the outset of their academic journey, and conveying the industry values (naturally I adapt the Amazon leadership principles of "learn and be curious", "earn trust", and so on - those that apply) - Networking: Facilitating connections with industry professionals and alumni to broaden their perspectives and opportunities. - Navigating the Job Landscape: Guiding students through the process of understanding the job market, identifying suitable roles, and preparing for them effectively. - Exploring Career Pathways: Educating students about the diverse career paths in industry, from principal engineering roles to management positions, offering a glimpse into potential career trajectories. - Management Training: Offering basic management training and resources to those interested in exploring leadership roles within industry. This includes providing information on courses, workshops, and seminars that can bolster their management skills. - Resource Sharing: Providing information about online platforms, industry publications, and professional networks that can offer insights into the industry job landscape. Additionally, I emphasize the importance of developing soft skills, such as teamwork, communication, and project management, which are invaluable in any industry setting. It's also essential to foster an entrepreneurial mindset, encouraging students to think innovatively and understand the business aspects of science and technology. Does this mean I discourage academic pursuits? Not at all. My own journey from a national lab and industry back to academia is a testament to finding one's fit based on personal preferences and aspirations. I support students interested in academia with clear insights into all career paths, ensuring they make informed decisions. Ultimately, my aim is to mentor professionals who contribute significantly to both industry and society, ready for the future's challenges and opportunities. And support them on their chosen pathway.