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For Companies At a Glance
- Tasks: Lead an AI team, productise ML models, and deploy innovative AI solutions.
- Company: Join a forward-thinking company at the forefront of AI and automation.
- Benefits: Enjoy hybrid work flexibility, with only one monthly on-site visit covered.
- 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 leadership experience required.
- Other info: Work with cutting-edge tech like Python, React, and cloud solutions.
The predicted salary is between 60000 - 84000 £ per year.
We are 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 tech stack mentioned in the job description. Brush up on your skills in Python, React, C++, and especially MLOps tools like Terraform and Docker. Being able to discuss these technologies confidently during interviews will show that you're a great fit for the role.
✨Tip Number 2
Highlight your experience with managing multiple production AI models. Prepare examples of how you've scaled and optimised performance in previous roles. This will demonstrate your capability to handle the responsibilities outlined in the job description.
✨Tip Number 3
Showcase your leadership and mentoring skills by discussing past experiences where you led a team or project. Be ready to explain how you balanced hands-on work with leadership duties, as this is crucial for the role.
✨Tip Number 4
Emphasise your ability to collaborate cross-functionally. Prepare to share instances where you worked with data engineers, DevOps, or product teams to bring AI solutions to life. This will highlight your teamwork skills and adaptability, which are key for this position.
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 AI 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 ability to drive AI strategy.
Showcase Relevant Projects: Include a section in your application that details relevant projects you've worked on. Highlight your experience with tools like GitHub, Terraform, and cloud deployment, as well as any orchestration tools you've used in CI/CD pipelines.
Highlight Leadership Experience: Since the role involves managing and scaling an expert team, be sure to highlight your leadership and mentoring skills. Provide examples of how you've successfully led teams and collaborated cross-functionally to deliver AI solutions.
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, be ready to 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
The role requires cross-functional collaboration, so be sure to mention your experience working with data engineers, DevOps, and product teams. Share specific instances where your collaborative efforts led to successful AI project outcomes.
