How to Get a Better AI Job After a Lay-Off or Redundancy

Contents

• Understanding Redundancy in AI & Tech

• Step 1: Process the Shock & Reset Mentally

• Step 2: Assess the Market & Identify Opportunities

• Step 3: Refresh Your AI CV Strategically

• Step 4: Power Up Your LinkedIn & Online Presence

• Step 5: Outreach—The Smart Way to Connect with Recruiters

• Step 6: Nail the Application Process

• Step 7: Upskill While You Job Hunt

• Step 8: Consider Contract & Remote Roles

• Step 9: Protect Your Finances & Mental Health

• Bonus: Top AI Employers Currently Hiring

• Final Thoughts: You’re Not Starting Over—You’re Starting Smart

Understanding Redundancy in AI & Tech

The tech sector is no stranger to fluctuations. Even highly skilled AI professionals—from machine learning engineers to data scientists and AI product managers—have experienced redundancies during turbulent economic periods or company shifts in strategy.

But remember: being made redundant is not a reflection of your worth or skills. In most cases, it’s a business decision unrelated to performance. With AI talent still in demand across healthcare, fintech, logistics, retail, defence, and more, this is a temporary setback with long-term opportunity.

Step 1: Process the Shock & Reset Mentally

Take a breather—then get strategic.

After being made redundant, it’s normal to feel disbelief, sadness, anxiety or even anger. Allow yourself space to feel it, talk to trusted friends or mentors, and avoid making rash decisions.

Then, shift to strategic mode:

• Write down your achievements in your last role. This will boost your confidence and help later with your CV and interviews.

• Identify what you enjoyed or didn’t—use this to refine your future job criteria.

• Remember: redundancy can be a redirection. Many AI professionals end up finding more meaningful, better-paid, or flexible roles as a result.

Step 2: Assess the Market & Identify Opportunities

Before firing off applications, do a targeted analysis of the AI job landscape. Trends shift fast—especially in AI.

Use these tactics:

• Check live vacancies on ArtificialIntelligenceJobs.co.uk

• Analyse demand on LinkedIn for your role type

• Use job alerts to see what skills employers are asking for

• Research which sectors are growing, e.g. generative AI, healthcare AI, AI in robotics, or AI policy & ethics

This helps you align your CV and learning plan with actual market needs—making you more attractive to recruiters.

Step 3: Refresh Your AI CV Strategically

Your CV needs to show relevance, impact, and adaptability—especially after redundancy.

What to include:

• A short professional summary focusing on your AI skills, sector experience, and aspirations.

• Clear evidence of value delivered (e.g. “Deployed a real-time ML model that reduced fraud by 40% in 3 months”).

• Highlight tools (e.g. TensorFlow, PyTorch, Python, AWS, MLFlow) and techniques (e.g. NLP, computer vision, reinforcement learning) relevant to your target roles.

• Add certifications (e.g. Coursera, edX, or Google Cloud AI) to show you’re current and proactive.

• Address the redundancy honestly but briefly in your cover letter or interview—focus on your achievements and what’s next.

Tip: Use AI tools like ChatGPT to help rewrite your CV bullet points for clarity and power.

Sample CV Bullet Points for AI Roles Post-Redundancy

For Machine Learning Engineers:

• Developed & deployed a predictive maintenance model using Python & Scikit-learn, reducing equipment downtime by 35%.

• Led migration of legacy ML pipelines to a scalable cloud environment using AWS SageMaker & Lambda functions.

For NLP Specialists:

• Fine-tuned BERT-based models to improve sentiment analysis accuracy by 17% on unstructured customer feedback.

• Built an entity recognition engine for legal documents, reducing manual processing time from 8 hours to 45 minutes.

For Data Scientists:

• Conducted exploratory data analysis (EDA) & model development for pricing optimisation, leading to a £1.2M increase in annual revenue.

• Created dashboards in Tableau & Power BI to track model performance metrics across business units.

For AI Product Managers:

• Collaborated with ML engineers to deliver a fraud detection system that reduced false positives by 40%.

• Managed roadmap for generative AI features, increasing enterprise adoption by 25% within 6 months.

Step 4: Power Up Your LinkedIn & Online Presence

Your LinkedIn is your digital CV, personal brand, and job lead generator all in one.

Optimise your profile:

• Update your headline with your target role, e.g. “AI Engineer | NLP | Deep Learning | Open to Work”

• Use the “Open to Work” badge

• Add a compelling “About” section summarising your skills, values, and goals

• Showcase projects in the “Featured” section (GitHub, Kaggle, blog posts)

• Ask ex-colleagues for recommendations—these build trust

Sample LinkedIn “About” Section:

AI Engineer | NLP & Deep Learning | Python | Looking for New Opportunities
I’m a hands-on AI engineer with over 5 years’ experience delivering machine learning solutions in sectors including fintech, healthcare, and e-commerce. I specialise in natural language processing, model deployment, and cloud-based ML infrastructure.

Recently impacted by redundancy due to company restructuring, I’m using this time to deepen my expertise in LLMs, LangChain, and real-world deployment techniques. I’m actively seeking new challenges in forward-thinking teams where AI drives real-world impact.

✅ NLP (BERT, spaCy, Hugging Face Transformers)
✅ ML Engineering (Python, TensorFlow, Scikit-learn)
✅ Cloud & MLOps (AWS, Docker, Git, MLFlow)

Let’s connect if you’re hiring—or if you’re working on exciting problems in applied AI.
Portfolio: [GitHub link]
Contact: [email address]

Step 5: Outreach—The Smart Way to Connect with Recruiters

Recruiters are a crucial part of your rebound. But rather than blasting out messages, tailor your outreach for better results.

Message to Recruiter (LinkedIn or Email):

Hi [Recruiter’s Name],
I’m reaching out as a recently available AI engineer with experience in NLP, Python, and cloud deployment. After a recent redundancy due to restructuring, I’m exploring new opportunities where I can contribute to innovative AI products.
I’ve attached my updated CV and LinkedIn profile below. Please let me know if there are any roles you’re working on that align with my skills.
Kind regards,
[Your Name]

Message to Hiring Manager (Direct Application):

Dear [Hiring Manager],
I’m applying for the Machine Learning Engineer role advertised on ArtificialIntelligenceJobs.co.uk. With a background in deploying production-grade ML models and a passion for building ethical, scalable AI systems, I’d love the chance to contribute to your team.
I’ve recently become available following a company restructure and am ready to hit the ground running.
Please find my CV attached. I’d welcome the opportunity to speak further.
Best regards,
[Your Name]

Step 6: Nail the Application Process

You don’t need to apply to 100 jobs. You need to apply strategically to 10–15 great ones.

For each application:

• Tailor your CV and cover letter to the job spec

• Mirror key phrases from the job ad (good for ATS systems)

• Highlight transferable projects (e.g. AI in finance can transfer to healthcare or logistics)

• Prepare for coding tasks, take-home projects, or tech interviews with tools like LeetCode, HackerRank, or Interviewing.io

• Always follow up 7–10 days after applying

Step 7: Upskill While You Job Hunt

Redundancy gives you the rare gift of time to learn without a full-time job in the way.

Top platforms to upskill in AI:

• Coursera: Industry-recognised certifications (e.g. DeepLearning.AI)

• edX: University-level courses from Harvard, MIT, IBM

• Udacity: Career-focused nanodegrees with mentorship

• Hugging Face: Free transformer and NLP training

• Kaggle: Real datasets and competitions to showcase work

• Fast.ai: Practical deep learning for coders

Step 8: Consider Contract & Remote Roles

Many companies hire contractors or remote workers as a flexible way to scale AI teams—especially post-budget cuts.

Benefits of contract/remote work:

• Higher short-term earnings

• Broader exposure to industries

• Option to pivot into freelance consulting

Check filters on ArtificialIntelligenceJobs.co.uk or freelance platforms like Toptal & Upwork.

Step 9: Protect Your Finances & Mental Health

Financial tips (UK-specific):

• Check if you’re entitled to redundancy pay, Universal Credit, or Jobseeker’s Allowance

• Explore retraining options via Jobcentre Plus

• Reduce non-essential spending

• Consider part-time or temp work while job hunting

Mental health tips:

• Create a balanced daily routine

• Stay connected with communities or mentors

• Be kind to yourself—everyone’s journey is different

Bonus: Top AI Employers Currently Hiring (UK 2025)

1. DeepMind

2. Babylon Health

3. Darktrace

4. Ocado Technology

5. Faculty AI

6. Revolut

7. BBC R&D

8. Amazon UK (AWS)

9. Graphcore

10. Tractable

11. Onfido

12. Meta UK

13. Cambridge Consultants

14. University spinouts (Oxford, Cambridge)

15. NHS AI Lab

Final Thoughts: A Better AI Role Could Be Next

Redundancy can be the beginning of something better—especially in a high-growth, high-demand field like artificial intelligence.

You now have:

• A chance to recalibrate your goals

• A clear plan to upgrade your skills & visibility

• A job market still hungry for your talent

At ArtificialIntelligenceJobs.co.uk, we believe that AI professionals who bounce back often bounce higher. Whether you’re looking for remote roles, mission-led work, or a step up in responsibility, your next chapter starts now.

Don’t just rebound—relaunch.

Want Personalised Help?

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• Our AI CV review service

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• Free guides on interview prep, upskilling, & career change

• Recruiter contact directory

👉 Visit: www.artificialintelligencejobs.co.uk