Engineering Career

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

3 things hiring managers (like me!) would change about your resume: 1. 𝗬𝗼𝘂𝗿 𝗦𝘂𝗺𝗺𝗮𝗿𝘆 𝗮𝘁 𝘁𝗵𝗲 𝗧𝗼𝗽 Hiring managers *want* to know if you’re a great fit so we know a phone screen is a good use of everyone’s time (*your time matters to us, too*). Rather than a paragraph with: -Seasoned [role type] with X years... -Enthusiastic and energetic professional... -Passion for growth... -Motivated by.... Hiring managers want to know about relevant results or impacts from your career, multilingual abilities, or the tools/technologies you have experience with (that are relevant to the role they're trying to fill) 𝗧𝗜𝗣: Try 3-5 bullet points instead of a paragraph - it'll help you avoid filler words 2. 𝗥𝗲𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀 𝗦𝗲𝗰𝘁𝗶𝗼𝗻 Most people use this space ineffectively. Some choose to list out soft skills like 'time management" or "collaboration" - hiring managers would rather have you share a bullet point about *how* your time management brought about a *result*. Other candidates list things like "CRM Software", "Learning Management Systems". The problem? Which ones? (you didn't give enough detail! This is like a clue in a resume mystery that most hiring managers don't have time to solve). And others list out specific like "Salesforce", "Adobe Captivate", "Seesaw"....but then never mention it anywhere else in their resume (leaving the hiring manager to wonder how and when you used these tools). 𝗧𝗶𝗽: Want your "skills" to stand out? You don't need a section. Instead, try bolding them and using them actively in your bullet point sentences instead of putting them in a section of their own. 3. 𝐒𝐡𝐚𝐫𝐞 𝐦𝐨𝐫𝐞 𝐭𝐡𝐚𝐧 𝐚 𝐥𝐢𝐬𝐭 𝐨𝐟 𝐣𝐨𝐛 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 Many job-seekers' experience sections look more like a job posting for their former roles than a list of accomplishments: "Delivered presentations to stakeholders" or "Conducted assessments to measure for understanding". Two questions to help improve: 1) 𝗗𝗼𝗲𝘀 𝘁𝗵𝗲 𝗲𝘅𝗮𝗺𝗽𝗹𝗲 𝘆𝗼𝘂'𝗿𝗲 𝗹𝗶𝘀𝘁𝗶𝗻𝗴 𝗵𝗮𝘃𝗲 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗷𝗼𝗯 𝘆𝗼𝘂 𝗮𝗿𝗲 𝘁𝗿𝘆𝗶𝗻𝗴 𝘁𝗼 𝗴𝗲𝘁? (𝘪𝘯 𝘰𝘵𝘩𝘦𝘳 𝘸𝘰𝘳𝘥𝘴, 𝘪𝘵 𝘮𝘢𝘺 𝘯𝘰𝘵 𝘣𝘦 𝘶𝘴𝘦𝘧𝘶𝘭 𝘵𝘰 𝘵𝘩𝘦 𝘩𝘪𝘳𝘪𝘯𝘨 𝘮𝘢𝘯𝘢𝘨𝘦𝘳 𝘵𝘰 𝘬𝘯𝘰𝘸 𝘺𝘰𝘶 𝘤𝘰𝘯𝘥𝘶𝘤𝘵𝘦𝘥 𝘢𝘴𝘴𝘦𝘴𝘴𝘮𝘦𝘯𝘵𝘴 𝘣𝘦𝘤𝘢𝘶𝘴𝘦 𝘵𝘩𝘢𝘵 𝘢𝘤𝘵𝘪𝘰𝘯 𝘥𝘰𝘦𝘴𝘯'𝘵 𝘩𝘢𝘷𝘦 𝘢𝘯𝘺𝘵𝘩𝘪𝘯𝘨 𝘵𝘰 𝘥𝘰 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘴𝘬𝘪𝘭𝘭𝘴 𝘯𝘦𝘦𝘥𝘦𝘥 𝘧𝘰𝘳 𝘵𝘩𝘦 𝘫𝘰𝘣 𝘺𝘰𝘶'𝘳𝘦 𝘢𝘱𝘱𝘭𝘺𝘪𝘯𝘨 𝘧𝘰𝘳) 2)Does your example show business impact? (𝗮𝗸𝗮, 𝗮𝗿𝗲 𝘆𝗼𝘂 𝘀𝗵𝗼𝘄𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀/𝗼𝘂𝘁𝗰𝗼𝗺𝗲 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗮𝗰𝘁𝗶𝗼𝗻𝘀?) -------------------------- 𝗝𝗼𝗯 𝗦𝗲𝗮𝗿𝗰𝗵 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀: linktr.ee/erinlewber

I constantly get recruiter reachouts from big tech companies and top AI startups- even when I’m not actively job hunting or listed as “Open to Work.” That’s because over the years, I’ve consciously put in the effort to build a clear and consistent presence on LinkedIn- one that reflects what I do, what I care about, and the kind of work I want to be known for. And the best part? It’s something anyone can do- with the right strategy and a bit of consistency. If you’re tired of applying to dozens of jobs with no reply, here are 5 powerful LinkedIn upgrades that will make recruiters come to you: 1. Quietly activate “Open to Work” Even if you’re not searching, turning this on boosts your visibility in recruiter filters. → Turn it on under your profile → “Open to” → “Finding a new job” → Choose “Recruiters only” visibility → Specify target titles and locations clearly (e.g., “Machine Learning Engineer – Computer Vision, Remote”) Why it works: Recruiters rely on this filter to find passive yet qualified candidates. 2. Treat your headline like SEO + your elevator pitch Your headline is key real estate- use it to clearly communicate role, expertise, and value. Weak example: “Software Developer at XYZ Company” → Generic and not searchable. Strong example: “ML Engineer | Computer Vision for Autonomous Systems | PyTorch, TensorRT Specialist” → Role: ML Engineer → Niche: computer vision in autonomous systems → Tools: PyTorch, TensorRT This structure reflects best practices from experts who recommend combining role, specialization, technical skills, and context to stand out. 3. Upgrade your visuals to build trust → Use a crisp headshot: natural light, simple background, friendly expression → Add a banner that reinforces your brand: you working, speaking, or a tagline with tools/logos Why it works: Clean visuals increase profile views and instantly project credibility. 4. Rewrite your “About” section as a human story Skip the bullet list, tell a narrative in three parts: → Intro: “I’m an ML engineer specializing in computer vision models for autonomous systems.” → Expertise: “I build end‑to‑end pipelines using PyTorch and TensorRT, optimizing real‑time inference for edge deployment.” → Motivation: “I’m passionate about enabling safer autonomy through efficient vision AI, let’s connect if you’re building in that space.” Why it works: Authentic storytelling creates memorability and emotional resonance . 5. Be the advocate for your work Make your profile act like a portfolio, not just a resume. → Under each role, add 2–4 bullet points with measurable outcomes and tools (e.g., “Reduced inference latency by 35% using INT8 quantization in TensorRT”) → In the Featured section, highlight demos, whitepapers, GitHub repos, or tech talks Give yourself five intentional profile upgrades this week. Then sit back and watch recruiters start reaching you, even in today’s competitive market.

This ENTRY LEVEL resume got interviews at Palantir Technologies, Amazon, Microsoft, Google & here are the reasons why: 1. Strategic Information Hierarchy: - Education is rightly placed at the top (May 2024 graduation). - Clear, bolded section headers (EDUCATION, EXPERIENCE, PROJECTS, ACHIEVEMENTS, TECHNICAL SKILLS) guide the reader's eye. - Consistent date and location formatting on the right margin keeps it tidy and easy to scan. (MAKE IT EASY FOR RECRUITERS!) 2. Quantifiable Achievements Everywhere: - "achieving a 23% reduction in latency" (Amazon) - "reduce API load by 30%" (Amazon) - "HackWashu Hackathon 1st Place" - Metrics demonstrate the impact of their work. 3. Action Oriented & Tech Specific Descriptions: - Starts bullet points with strong verbs: "Optimized," "Implemented," "Directed," "Spearheaded," "Engineered," "Developed." - Specific technologies (Spring MVC, ElasticSearch, DynamoDB, ASP.NET MVC, React Native, C++, Python, GPT) are embedded WITHIN their bullet points. 4. Clear Progression & Diverse Skill Application: - Internship experiences show solid software development fundamentals in different environments (Amazon, U.S. Bank). - Projects demonstrate versatility across different domains: full-stack mobile app development (FitnessPal), systems programming (CLI Replication), algorithmic trading (WUSIF Algo Trading), and AI application (Hackathon). - Shows growth through application of diverse skills and technologies in practical settings. I've been lucky enough to have mentors who have shared their resumes with me and I want to do the same for others. Find what VERIFIED resumes landed people interviews at Google, Meta, Microsoft: https://bit.ly/3HKbsOO Not every resume should look like this. I’m sharing it because this is what’s actually working in today’s job market. For me, I never had anyone share their resumes that got interviews at companies. It was always a black box. And if this post helps even one person get a foot in the door, then I’ll keep sharing.

I asked 7 levels of engineers to share the most important skill for their level. L3 New Grad (Uriel Sejas): 🏋♀️ Skill: Learn from existing patterns to solve common problems. 🦉 Advice: Leverage engineers on other teams who may help unblock you. L4 Mid-level Engineer (Dipika Tiwari): 🏋♀️ Skill: Efficient log analysis to identify and debug issues. 🦉 Advice: Keep notes on your work so you become increasingly self-sufficient. L5 Senior Engineer (Richard Chen): 🏋♀️ Skill: Align project expectations and ensure projects benefit both the company and your growth. 🦉 Advice: Build strong relationships with people you work with, helping them where possible. L6 Staff Engineer (Sam Nguyen): 🏋♀️ Skill: Level up your team and ensure they internalize feedback to become independent. 🦉 Advice: Learn the problems in the org by talking to many people. L7 Senior Staff Engineer (Kaushik Gopal): 🏋♀️ Skill: Instead of just doing eng work, spend time identifying, executing, and measuring impact. 🦉 Advice: Talk to different stakeholders (business, customer support, PM) to identify areas where the company struggles. L8 Principal Engineer (Chantat Eksombatchai): 🏋♀️ Skill: Effective technical communication to delegate tasks effectively and collaborate with others. 🦉 Advice: Principal engineers are role models for an entire org and therefore determine the culture. L9 Distinguished Engineer (Andrew Zhai): 🏋♀️ Skill: Combine strong business acumen with technical expertise to lead large, impactful projects. 🦉 Advice: Pursue the most impactful projects and navigate the company to make them happen. Full video: https://lnkd.in/gbCKPPji

Your resume has 7 seconds to prove you're worth the six figures you’re asking for. Many people waste those seconds on outdated formats and weak bullets. After helping 100s of high earners land dream roles, I've discovered what separates winning resumes from the 90% that get ignored. It's not about fancy designs or buzzwords. It's about strategic positioning and quantified impact. The professionals landing $200K+ offers aren't lucky. They're using AI to help with their job search. Including for the resume. Here's how they approach resumes differently: Instead of "Managed 25 person team and improved processes that reduced costs…" They write: "Led 25-person team through digital transformation, reducing costs by 32% ($2.1M) while increasing output 40%" Instead of generic summaries that blend in… They craft something like: "Senior Engineer with 10 years building scalable systems. Reduced latency 60% for 50M users. Architected platforms at 3 unicorns…" The difference? Specificity. Metrics. Strategic thinking. Every bullet proves your business impact. Every line shows measurable results. Every word earns its place. While others submit the same resume 100 times, you'll customize it in minutes using these prompts. While they hope keywords match, you'll know exactly what hiring managers see. While they list responsibilities, you'll showcase transformational results. Your expertise deserves better than generic templates. Your achievements deserve to be quantified. Save this post. Use it to upgrade your resume. Share it to help someone in your network. Stop underselling yourself. Start landing interviews. And give me a follow me for more strategies to win the $200K–$500k job market.

This is one of the most important things I’ve learned about resumes, and most don’t do it. Not doing this can hurt your chances of getting an interview 👇 Your resume 𝐬𝐡𝐨𝐮𝐥𝐝 𝐧𝐨𝐭 𝐛𝐞 a description of what you are 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 for. Your resume 𝐬𝐡𝐨𝐮𝐥𝐝 𝐛𝐞 a collection of your 𝐚𝐜𝐜𝐨𝐦𝐩𝐥𝐢𝐬𝐡𝐦𝐞𝐧𝐭𝐬 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 to the job you are applying for! Here's a simple example: A Project Manager's resume that describes what they are 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 for looks like this: - Delivered the project on time and within budget. - Communicated updates regularly to all stakeholders. This is a terrible way to "stand out" - In this example, every Project Manager is responsible for delivering projects on time and budget, and for communicating with stakeholders. In other words, there's nothing 𝐮𝐧𝐢𝐪𝐮𝐞 about this person's resume. Your resume has to show: - Evidence that you have the experience they are looking for (Tailored resume) - Evidence of the value you bring to the team (Your past accomplishments) To write a resume that 𝐬𝐭𝐚𝐧𝐝𝐬 𝐨𝐮𝐭, here’s what you should do 👇 Write 𝐚𝐜𝐜𝐨𝐦𝐩𝐥𝐢𝐬𝐡𝐦𝐞𝐧𝐭𝐬, not what you were responsible for : - What did you do? - What was the impact? - How did you accomplish it? Use the “𝐗 + 𝐘 + 𝐙” formula to write accomplishments: “Accomplished [𝐗] as measured by [𝐘], by doing [𝐙]” 🛑 Instead of writing: “Delivered a project on time and budget” ✅ Write this: 𝐀𝐜𝐜𝐨𝐦𝐩𝐥𝐢𝐬𝐡𝐞𝐝 [𝐗]: “Launched ____ project” 𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐝 𝐛𝐲 [𝐘]: “1 month ahead of schedule and increasing ROI by Z%” 𝐁𝐲 𝐝𝐨𝐢𝐧𝐠 [𝐙]: “, by creating a new communication process that allowed low and medium risk tickets to be pre-appproved, reducing friction during development” Together X + Y + Z: “Launched ___ project 1 month ahead of schedule and increasing ROI by Z%, , by creating a new communication process that allowed low and medium risk tickets to be pre-appproved, reducing friction during development” 𝐀𝐜𝐜𝐨𝐦𝐩𝐥𝐢𝐬𝐡𝐦𝐞𝐧𝐭𝐬 help you show that you have the experience companies look for in 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 of a project that had impact to customers, your team or the organization. 𝐓𝐚𝐢𝐥𝐨𝐫𝐢𝐧𝐠 your 𝐚𝐜𝐜𝐨𝐦𝐩𝐥𝐢𝐬𝐡𝐦𝐞𝐧𝐭𝐬 to the job you are applying to will increase your chances of getting an interview. Adding more colors, graphs and random keywords will not. A few extra tips as you go through your accomplishments: 1. Not every accomplishment will have a number (impact). It’s ok, try to have as many as possible. 2. Accomplishments tailored to the job you are applying to >>>> accomplishments you believe are the most important. 3. You can skip the XYZ formula and instead write them as: Verb in past tense + what you did + the impact it had. ------ 🚀 Need help with your resume or Product Management interviews? Check out my comment below for THE BEST resources 👇 #productmangement #resume

Here’s something I wish I understood earlier: Data Science and Computer Science may overlap, but they open very different doors. ➜ 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 combines statistics, programming, and domain expertise to uncover patterns that power forecasting, big-data analytics, and fraud detection. ➜ 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 dives into algorithms, data structures, and systems design so you can build scalable software, secure networks, and AI infrastructure. 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆: • Choose Data Science if you love turning raw numbers into actionable insights. • Choose Computer Science if you’re driven to architect the code and systems behind those insights. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: Picking the right path from the start lets you focus on the skills that fuel real impact—and accelerates your growth.

A client of mine landed a $125k Machine Learning Engineering entry-level role before they graduated from their master's program. Here’s how we did it: 1) Building a Strong Foundation (First 6 Months) - Daily Coding Practice and Projects: Dedicated 100% of their time to building projects and honing coding skills. - Maximizing Chances: We started our partnership a year before graduation to ensure no time was wasted. - Relevant Experience: They had 3+ years of experience as a SWE in another country but wanted to overcome the lack of ML experience. - Industry-Level Project: Created a comprehensive Full-stack Industry-Level Personal Project focused on Full-stack, MLOps, and Cloud deployment. 2) Portfolio Optimization (6 Months Before Graduation) - Highlighting Transferable Skills: Showcased skills from previous roles. - Showcasing Value: Positioned themselves as an experienced data professional, not just a fresh graduate. - Standout READMEs: Made their projects compelling and easy to understand with detailed and attractive READMEs. 3) Strategic Job Search (6 Months Before Graduation) - Targeted Companies: Created a list of 40 desired companies. - Building Relationships: Started networking early to avoid desperation. - Focused Referrals: Spent all job searching time on getting referrals from people in target companies. 4) Mock Interviews - Recurring Practice: Focused on live coding, case studies, and system design interviews to ensure readiness. Results: - ~35 referrals - ~27 referrals directly to hiring managers - ~15 interviews - Many screenings - 2 offers of $125k+ This is not an average expected value, and every job search can look different. But remember, you only need 1 yes. Ready to land your next role? Let's make it happen! If you read this far, thank you for the support! Now I want to give back to you! Share what your current job search struggle is and I will respond to every comment with actionable tips. P.S. If you are currently sending applications make sure to include your data so I can give you actionable data-driven tips. Here is an example: ----------- I have been job searching for 3 months: ~200 applications 6 screenings 0 referrals 1 Interview 0 final rounds 0 offers My problem is _____. ----------- Share yours in the comments! ------------------------ ➕ Follow Jaret André for more daily data job search tips. 🔔 Hit the bell icon to be notified of job searchers' success stories.

What would I do today if I recently decided I wanted to start a career as a software engineer? This topic has come up in a couple different spaces I'm involved in, so I wanted to put my thoughts out here. These are the steps I recommend whether you're a college student, considering a boot camp, or just taking the self-taught route, although the process will be a bit different for each depending on the phase of life you are in. First, find out which domain is interesting to you. Do you want to build websites? Do you love munging data? Are you more behind the scenes? Love science? Math? Tech has it all. Find a few areas that seem interesting to you based on your personality and learn more about them. Once you've found what interests you, you need to figure out what skills you need to learn in order to land a job in that field. I'm not saying to go learn the skills - I'm saying to just figure out what they are. Start by looking at companies in your area (they're more likely to hire you), look at job postings online, and try to message some devs. I've found that most are pretty friendly. "Hey I see you're a front-end developer, what tech stack does your team use? I'm trying to figure out what I need to start learning." Most would be receptive to that. After you narrow down a few key technical areas to start learning, start learning! Start small - learn the mechanics. Try to get stuff installed on your computer and print out some numbers. Don't jump right into tutorials that you blindly follow. Be uncomfortable for a little bit. Learn something basic, then change it up a bit and try to do a little more on your own. Once you've spent a week or two feeling like, "what the hell did I get myself into?" You've begun! You'll feel like that a lot. (I still feel like that sometimes). At that point, start a tutorial. Build a small project. This project won't get you a job. Now build 10 more, but after you're second one, join a community and try to find a mentor (I'd recommend Code Connector :D). The community will be your single biggest asset while you are learning, because there are usually a lot of people in there who will help you grow. Dive in and get to know people, and keep building those 10 projects. None of those 10 projects will get you a job. I'll reiterate that. After you start to feel comfortable with the smaller projects, implement an idea. You like pokemon? Build something around that? You like dogs? Build something around that. This one should be a bit more real. Try to learn how to do things correctly on this one. If it sucks and you're really struggling - that's good! You should! It means you're growing. You should sit in that for awhile. You should really try to understand this project. At this point, you're getting closer. You might sit in that state for 6 months, or a year and a half. It's a hard road, but it's a fun job. If you ever want to talk about getting started, shoot me a message! Hope this helps. #softwareengineering