At a Glance
- Tasks: Develop and deploy advanced AI algorithms to automate processes and extract insights.
- Company: Innovative organisation focused on impactful public sector projects.
- Benefits: Competitive salary, generous leave, professional development, and hybrid working options.
- Other info: Inclusive culture that values diversity and offers excellent career growth opportunities.
- Why this job: Make a real difference with cutting-edge AI technology in a collaborative environment.
- Qualifications: Expertise in machine learning, AI technologies, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 ÂŁ per year.
Work on impactful public sector and mission‑critical digital projects that make a positive difference to people’s lives. This organisation specialises in solving complex technical challenges using modern tools, emerging technologies, and innovative thinking. As a Machine Learning Engineer (AI), you will research, develop, and test advanced AI algorithms, models, and technologies that enable organisations to automate processes and extract meaningful insights from data. You will build complex machine learning models, design and manage MLOps pipelines, and ensure models remain performant, secure, and scalable in production environments. The role also includes mentoring junior team members, influencing technical decisions, and solving complex, non‑routine technical problems. The culture is inclusive, collaborative, and innovation‑driven. The organisation values proactive, positive‑thinking individuals who enjoy tackling technical challenges.
Role Objectives
- Model Development and Delivery: Design, build, test, and deploy complex machine learning models. Select appropriate modelling approaches for product and service use cases. Ensure models meet performance, scalability, and quality standards.
- MLOps and Deployment: Design and manage robust MLOps pipelines, including CI/CD processes. Implement monitoring, retraining, and lifecycle management. Deploy models into production environments and validate performance. Ensure models remain safe, secure, and effective in live systems.
- Advanced Technical Problem Solving: Act as a subject matter expert for complex, non‑routine machine learning challenges. Develop innovative solutions to high‑risk or ambiguous problems. Customise, optimise, retrain, and maintain existing models.
- Integration and Collaboration: Work cross‑functionally to integrate machine learning models into existing systems. Collaborate with engineers, data scientists, and technical stakeholders. Ensure production systems meet reliability and security standards.
Requirements
- Broad expertise in machine learning algorithms, frameworks, and best practices.
- Experience planning and conducting research activities within AI or generative AI domains.
- Ability to evaluate emerging AI technologies for business relevance and feasibility.
- Experience delivering complex proofs of concept and experimental prototypes.
- Recognised technical authority within AI or generative AI.
- Strong data science capability supporting model development.
- Proven experience building, deploying, and managing complex machine learning systems.
Inclusion Statement
Candidates are encouraged to apply even if they do not meet every requirement. The organisation values diversity and welcomes applications from individuals across all backgrounds, including underrepresented communities. Reasonable adjustments can be made throughout the recruitment process to support individual needs.
Security Requirements
This role requires eligibility for government‑level security clearance. Candidates must have the legal right to work in the UK without sponsorship and meet residency requirements for clearance eligibility.
Benefits
- Competitive salary reviewed annually.
- Employer pension contribution starting at 5 percent, increasing with tenure.
- Group Life Assurance.
- 25 days annual leave plus bank holidays, with option to buy or sell leave.
- Two paid volunteering days per year.
- Fully funded professional certifications and paid study leave.
- Annual personal development allowance.
- Access to coaching and professional training.
- Private medical insurance.
- Hybrid working with home office allowance.
- Cycle to Work scheme.
Lead Machine Learning Engineer, AI employer: Virtual Hire Staffing
Contact Detail:
Virtual Hire Staffing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Machine Learning Engineer, AI
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to machine learning and AI. You never know who might be looking for someone just like you!
✨Show Off Your Skills
Create a portfolio showcasing your projects and models. Whether it's GitHub repos or a personal website, let your work speak for itself. This is your chance to shine and demonstrate your expertise!
✨Ace the Interview
Prepare for technical interviews by brushing up on your algorithms and problem-solving skills. Practice common machine learning scenarios and be ready to discuss your past experiences. Confidence is key!
✨Apply Through Us!
Don’t forget to apply through our website! We’re all about finding the right fit, and we want to see your application. Plus, it’s a great way to get noticed by our team directly!
We think you need these skills to ace Lead Machine Learning Engineer, AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Lead Machine Learning Engineer role. Highlight your expertise in machine learning algorithms and any relevant projects you've worked on, especially those that demonstrate your problem-solving abilities.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for our team. Don’t forget to mention any experience you have with MLOps and collaboration across teams.
Showcase Your Projects: If you've built or deployed any machine learning models, make sure to include them in your application. We love seeing real-world examples of your work, so link to your GitHub or any relevant portfolios that showcase your skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our innovative team!
How to prepare for a job interview at Virtual Hire Staffing
✨Know Your Algorithms
Brush up on your knowledge of machine learning algorithms and frameworks. Be ready to discuss specific models you've built, the challenges you faced, and how you overcame them. This shows your technical depth and problem-solving skills.
✨Showcase Your MLOps Experience
Prepare to talk about your experience with MLOps pipelines. Highlight any CI/CD processes you've implemented and how you've ensured model performance in production. This will demonstrate your ability to manage complex systems effectively.
✨Be a Team Player
Since collaboration is key in this role, think of examples where you've worked cross-functionally. Discuss how you’ve integrated machine learning models into existing systems and collaborated with engineers and data scientists to achieve common goals.
✨Embrace the Challenge
This organisation values proactive individuals who enjoy tackling technical challenges. Prepare to share instances where you've developed innovative solutions to complex problems. Show your enthusiasm for problem-solving and your ability to think outside the box.