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Lesson 13 of 15

Networking & Job Search Strategy

LinkedIn Networking & Cold Outreach

5 min read

Building Your LinkedIn Network

Who to Connect With:

Priority 1: ML Engineers at Target Companies

  • Send connection request with personalized note
  • Mention specific project or post of theirs
  • Keep it short (2-3 sentences)

Priority 2: Recruiters

  • Internal recruiters at FAANG+
  • Agency recruiters specializing in ML/AI
  • Follow companies' career pages

Priority 3: Alumni & Community

  • Your university alumni in ML roles
  • Members of ML communities (r/MachineLearning, Kaggle)
  • People you met at meetups/conferences

Don't Spam:

  • Avoid "Open Networker" mass connections
  • Don't connect with competitors' employees randomly
  • Quality > quantity (500 relevant > 5000 random)

Cold Outreach Message Template

Structure:

  1. Personalized opening (why them?)
  2. Brief intro (who are you?)
  3. Specific ask (what do you want?)
  4. Easy out (respect their time)

Example: Reaching ML Engineer

Hi [Name],

I came across your post about deploying LLMs on AWS Lambda -
the cold start optimization technique you shared was brilliant!

I'm transitioning into ML engineering and have been building
projects in LLM deployment (here's my demo: [link]).

Would you be open to a 15-minute chat about your career path
into ML at [Company]? I'm specifically curious about the types
of projects junior MLE's work on.

No worries if you're too busy - I know your time is valuable!

Best,
[Your Name]

Example: Reaching Recruiter

Hi [Name],

I saw [Company] is hiring for ML Engineers and I'm very
interested in the role (Req #12345).

I have 3 ML projects deployed in production, including an
LLM-powered Q&A system (live demo: [link]) and a churn
prediction API serving 1000+ requests/day.

Would you be the right person to discuss this role? If not,
could you point me to the hiring manager?

Thank you!
[Your Name]

What Works (and What Doesn't)

Good Opening Lines: ✓ "Your article on MLOps best practices helped me improve my deployment workflow" ✓ "I noticed you worked on [specific project] - I'm building something similar" ✓ "Fellow [University] alum here, saw you're now at [Company]"

Bad Opening Lines: ✗ "I see you work at Google, can you refer me?" ✗ "I want to learn ML, can you mentor me?" ✗ "I'd love to pick your brain" (vague ask) ✗ Generic LinkedIn auto-message

The Ask: Be Specific

Too Vague: "Can we chat about ML careers?" → They don't know what to prepare

Specific & Actionable: "Can we chat for 15 minutes about:

  1. How you transitioned from SWE to MLE
  2. What your interview process was like at [Company]
  3. Advice on portfolio projects for junior roles"

Follow-Up Strategy

If No Response After 1 Week:

  • Send a polite bump (only once)
  • Add value: "Also wanted to share this article on [topic you discussed]"

If They Respond:

  • Reply within 24 hours
  • Suggest 2-3 specific times for call
  • Send calendar invite

After the Call:

  • Send thank-you message within 24 hours
  • Mention specific advice they gave
  • Keep them updated on your progress (don't disappear)

Providing Value First

Before Asking for Help:

  • Engage with their posts (thoughtful comments)
  • Share their articles
  • Offer to beta test their projects
  • Introduce them to relevant connections

Example:

Hi [Name],

I saw you're looking for beta testers for your new ML
monitoring tool. I'd love to try it on my churn prediction
API and give detailed feedback.

Also, I recently connected with [Person] who works on similar
problems at [Company] - happy to introduce you if helpful.

[Your Name]

Maintaining Relationships

Stay Top of Mind:

  • Share interesting ML papers/articles
  • Congratulate on promotions/new roles
  • Update them on your job search progress
  • Don't only reach out when you need something

The 3-Touch Rule: Engage 3 times before asking for a favor:

  1. Connect with personalized note
  2. Comment on their post
  3. Share relevant article → Then ask for informational interview

LinkedIn Activity Strategy

Post Consistently (2-3 times/week):

  • Share ML project updates
  • Lessons learned from building projects
  • Interesting papers you read
  • Career journey milestones

What to Post: ✓ "Just deployed my LLM chatbot - here's what I learned about prompt engineering [link]" ✓ "Reduced model inference time by 60% using quantization - thread with code snippets" ✓ "Completed Andrew Ng's MLOps course - key takeaways for production ML"

What NOT to Post: ✗ Generic motivational quotes ✗ Political opinions ✗ Complaints about job search ✗ Oversharing personal life

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Quiz

Module 5: Networking & Job Search Strategy

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