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For Companies At a Glance
- Tasks: Deploy AI/ML solutions and operationalise models for diverse clients.
- Company: Leading technology consultancy with a focus on innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact in the AI/ML space.
- Qualifications: Experience in MLOps, strong AWS skills, and proficiency in Python required.
- Other info: Exciting projects with excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
A leading technology consultancy is seeking an experienced Machine Learning Operations Engineer to help deploy AI/ML solutions into production environments across a range of client engagements. This role is focused on operationalising models (MLOps / AIOps), rather than building ML applications from scratch.
Key Responsibilities
- Design and develop machine learning operational processes across diverse client environments
- Analyse client requirements and provide clear technical recommendations
- Manage the full ML lifecycle, including data selection, model deployment, operationalisation, and monitoring
- Develop Infrastructure as Code for ML platforms using AWS CDK
- Collaborate closely with data scientists to productionise ML models
Required Experience & Skills
- Proven experience deploying AI/ML models into production (MLOps / AIOps)
- Strong AWS experience (other cloud platforms will not be considered)
- Experience with CI/CD pipelines for ML/DL models
- Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch)
- Experience with container technologies (Docker, Kubernetes)
- Consultancy or client-facing experience preferred
- Strong communication and stakeholder management skills
Qualifications
- IT / Technology-related degree (e.g. Computer Science, Engineering, Mathematics or similar)
- Minimum 2:1 classification (or equivalent)
- Bachelors degree or higher required
Machine Learning Engineer employer: Lynx Recruitment Limited
Contact Detail:
Lynx Recruitment Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with AI/ML. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects. Whether it's a GitHub repo or a personal website, let potential employers see what you can do with AWS and Python.
✨Tip Number 3
Prepare for interviews by brushing up on common ML operational questions. We recommend practising your answers to technical scenarios and being ready to discuss your experience with CI/CD pipelines and container technologies.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with MLOps and AWS. We want to see how you've deployed AI/ML models in production, so be specific about your achievements and the technologies you've used.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about operationalising ML models and how your skills align with our needs. Keep it concise but impactful!
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work with CI/CD pipelines, Python libraries, and container technologies. We love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Lynx Recruitment Limited
✨Know Your MLOps Inside Out
Make sure you brush up on your MLOps knowledge before the interview. Be ready to discuss your experience with deploying AI/ML models into production, and have specific examples at hand. This will show that you understand the operational side of machine learning, which is crucial for the role.
✨AWS Expertise is Key
Since strong AWS experience is a must-have, ensure you can talk confidently about your work with AWS services. Familiarise yourself with Infrastructure as Code using AWS CDK, and be prepared to explain how you've used it in past projects. This will demonstrate your technical prowess and readiness for the job.
✨Showcase Your CI/CD Knowledge
Be ready to discuss your experience with CI/CD pipelines for ML/DL models. Prepare to explain how you've implemented these processes in previous roles, and think about any challenges you faced and how you overcame them. This will highlight your problem-solving skills and practical experience.
✨Communication is Crucial
As this role involves collaboration with data scientists and client-facing interactions, practice articulating your thoughts clearly. Think of examples where you've successfully managed stakeholder expectations or communicated complex technical concepts to non-technical audiences. This will showcase your strong communication skills, which are essential for the position.
