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- Tasks: Build and maintain ML pipelines, deploy models, and ensure compliance in a regulated environment.
- Company: Join a leading insurance company focused on innovation and technology.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make an impact in the insurance sector using cutting-edge ML technologies.
- Qualifications: Strong MLOps and ML Engineering background with Python expertise.
- Other info: Work in a dynamic team with excellent career advancement opportunities.
The predicted salary is between 43200 - 72000 £ per year.
Details:
- 6 months IR35: Outside
- Location: London (1 day/month)
- Start: ASAP
Role:
- Build and maintain end-to-end ML pipelines
- Deploy models into production using CI/CD, containers, and cloud tooling
- Implement monitoring, drift detection, and observability
- Develop retrieval/LLM components using Python, LangChain/LlamaIndex, and vector DBs
- Work with Data Science teams to scale and operationalise models
- Ensure compliance and governance for models in a regulated insurance environment
Requirements:
- Strong MLOps + ML Engineering background
- Python, ML pipelines, CI/CD, orchestration, monitoring
- Experience with LLM/NLP integration
- Knowledge of vector search & embeddings
- Enterprise/regulated experience
- Insurance domain experience is essential
- Must have full right to work in the UK (no sponsorship)
MLOps / ML Engineer in London employer: Opus Recruitment Solutions
Contact Detail:
Opus Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps / ML Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the MLOps and ML Engineering space on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML pipelines and deployment. This gives us a tangible way to see what you can do.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss your experience with CI/CD, containers, and cloud tooling. We want to see your expertise shine!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace MLOps / ML Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your MLOps and ML Engineering experience. Use keywords from the job description to show we’re a perfect match for the role.
Showcase Relevant Projects: Include specific projects where you've built and maintained ML pipelines or deployed models. This gives us a clear picture of your hands-on experience and skills.
Highlight Compliance Knowledge: Since this role is in a regulated insurance environment, mention any experience you have with compliance and governance in your applications. It’s a big plus for us!
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 don’t miss out on any updates!
How to prepare for a job interview at Opus Recruitment Solutions
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, CI/CD, and cloud tooling. Brush up on your knowledge of ML pipelines and how to deploy models into production, as these are crucial for the role.
✨Showcase Your Experience
Prepare specific examples from your past work that demonstrate your MLOps and ML engineering skills. Highlight any projects where you’ve implemented monitoring or drift detection, especially in a regulated environment like insurance.
✨Understand the Business Context
Familiarise yourself with the insurance domain and how ML can be applied within it. Being able to discuss how your technical skills can solve real-world problems in this sector will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s current ML initiatives and challenges they face. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
