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- Tasks: Lead an AI team, productise ML models, and deploy innovative AI solutions.
- Company: Join a cutting-edge AI & Automation Centre of Excellence focused on transformative technology.
- Benefits: Enjoy hybrid work flexibility, with only one monthly on-site visit covered by expenses.
- Why this job: Shape the future of AI while managing impactful projects and leading a talented team.
- Qualifications: Strong expertise in AI/ML, MLOps, and experience with multiple production AI models required.
- Other info: Explore the latest in AI automation and collaborate across teams for real-world impact.
The predicted salary is between 72000 - 108000 £ per year.
We're searching for a Senior AI Engineer to lead a growing AI team within our clients' AI & Automation Centre of Excellence. You’ll be responsible for productizing ML models, managing MLOps infrastructure, and deploying cutting-edge AI solutions at scale.
What’s in it for you?
- Tech Stack: Python, React, C++, LLMs, NLP, MLOps, LangChain, Terraform, Docker, Cloud ☁
- Impact: Oversee 30-40 production models, drive AI strategy, and shape their AI-first future
- Leadership: Manage & scale an expert team, balancing hands-on work with leadership
- Hybrid Flexibility: London/Brighton HQ (only once per month on-site, expenses covered!)
What we’re looking for:
- Strong AI/ML expertise: experience in LLMs, NLP, agentic AI, and deep learning frameworks like PyTorch & TensorFlow
- MLOps & DevOps knowledge: GitHub, Terraform, orchestration tools, cloud deployment & CI/CD pipelines
- Experience managing multiple production AI models: handling 30-40 models, scaling, and optimizing performance
- Leadership & mentoring skills: ability to manage and grow a high-performing AI team
- Cross-functional collaboration: working with data engineers, DevOps, and product teams to bring AI solutions to life
- R&D mindset: comfortable exploring the latest in AI automation, agentic frameworks (LangGraph), and real-world AI deployment
Senior ML Engineer employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Python, TensorFlow, and MLOps tools. Having hands-on experience or projects showcasing these skills can set you apart from other candidates.
✨Tip Number 2
Demonstrate your leadership abilities by sharing examples of how you've successfully managed teams or projects in the past. Highlight any experience you have in mentoring others, as this is a key aspect of the role.
✨Tip Number 3
Showcase your ability to collaborate across different functions. Prepare to discuss instances where you've worked with data engineers or product teams to implement AI solutions, as this will be crucial for the role.
✨Tip Number 4
Stay updated on the latest trends in AI and ML, particularly in areas like LLMs and agentic AI. Being able to discuss recent advancements or your thoughts on future developments can demonstrate your R&D mindset and passion for the field.
We think you need these skills to ace Senior ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML, particularly in LLMs, NLP, and deep learning frameworks like PyTorch and TensorFlow. Emphasise any leadership roles you've held and your experience managing multiple production models.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your skills align with the company's goals. Mention specific projects where you've productised ML models or managed MLOps infrastructure, showcasing your impact.
Showcase Relevant Projects: Include a portfolio or a section in your CV that details relevant projects you've worked on. Highlight your experience with tools like GitHub, Terraform, and cloud deployment, as well as any successful collaborations with cross-functional teams.
Prepare for Technical Questions: Anticipate technical questions related to AI/ML and MLOps during the interview process. Brush up on your knowledge of orchestration tools, CI/CD pipelines, and the latest trends in AI automation to demonstrate your expertise.
How to prepare for a job interview at DeepRec.ai
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with the tech stack mentioned in the job description, particularly Python, LLMs, and MLOps. Highlight specific projects where you've successfully productised ML models or managed MLOps infrastructure.
✨Demonstrate Leadership Skills
Since the role involves managing a team, share examples of how you've led teams in the past. Discuss your approach to mentoring and how you balance hands-on work with leadership responsibilities.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in deploying AI solutions at scale and how you overcame them, especially in relation to managing multiple production models.
✨Emphasise Collaboration Experience
Highlight your ability to work cross-functionally with data engineers, DevOps, and product teams. Share specific instances where collaboration led to successful AI project outcomes, showcasing your communication and teamwork skills.
