Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Deploy and scale ML models while collaborating with clients and teams.
- Company: Join a fast-growing AI consultancy based in vibrant Manchester City Centre.
- Benefits: Enjoy 25 days holiday, a personal L&D budget, and a pension plan.
- Why this job: Tackle real-world AI challenges in a collaborative, innovative environment.
- Qualifications: 3+ years in Data Science/ML, strong Python skills, and familiarity with ML frameworks.
- Other info: Opportunity for open source contributions and learning new tech.
The predicted salary is between 43200 - 72000 £ per year.
We’re hiring a Senior Machine Learning Engineer (MLOps) to join an established AI consultancy based in Manchester City Centre (3 days on-site). If you\’re passionate about productionising machine learning and want to work on real-world AI challenges, this could be the role for you.
What you’ll be doing:
- Collaborating with clients to deploy and scale ML models
- Working closely with DS/ML teams in a highly collaborative, pair-programming environment
- Taking ownership of features and running sprint planning sessions
- Contributing to projects across research, prototyping, and production
What we’re looking for:
- 3+ years of experience in a Data Science / Machine Learning / Engineering role
- Strong Python skills and experience writing production-grade code
- Familiarity with ML frameworks (TensorFlow, PyTorch, Keras, SKLearn)
- Proficiency with Git, Unix/Linux, Docker
- Cloud experience (AWS, Azure, or similar)
#J-18808-Ljbffr
Senior MLOps Engineer employer: Gravitas Recruitment Group (Global) Ltd
Contact Detail:
Gravitas Recruitment Group (Global) Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps Engineer
✨Tip Number 1
Make sure to showcase your experience with ML frameworks like TensorFlow and PyTorch during networking events or meetups. Engaging in conversations about these technologies can help you connect with potential colleagues or employers who value hands-on experience.
✨Tip Number 2
Join online communities or forums related to MLOps and machine learning. Participating in discussions or sharing your insights can help you build a reputation in the field, making it easier for recruiters to notice you when they’re looking for candidates.
✨Tip Number 3
Consider contributing to open-source projects that focus on MLOps or machine learning. This not only enhances your skills but also demonstrates your commitment to the field, which can be a significant advantage when applying for the Senior MLOps Engineer position.
✨Tip Number 4
Prepare to discuss your experience with cloud platforms like AWS or Azure in detail. Being able to articulate specific projects where you've deployed ML models in the cloud will set you apart from other candidates and show your practical knowledge.
We think you need these skills to ace Senior MLOps Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Science and Machine Learning. Emphasise your strong Python skills and any familiarity with ML frameworks like TensorFlow or PyTorch, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for productionising machine learning. Mention specific projects where you've collaborated with teams to deploy ML models, showcasing your ability to work in a pair-programming environment.
Showcase Relevant Experience: When detailing your work history, focus on your 3+ years of experience in relevant roles. Highlight any cloud experience you have with AWS or Azure, and mention any open-source contributions if applicable.
Proofread and Edit: Before submitting your application, carefully proofread your documents. Check for any grammatical errors or typos, and ensure that all information is clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at Gravitas Recruitment Group (Global) Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and the ML frameworks mentioned in the job description. Bring examples of your production-grade code and be ready to explain your thought process behind it.
✨Demonstrate Collaboration Experience
Since the role involves working closely with Data Science and Machine Learning teams, share specific examples of how you've successfully collaborated in a team setting. Highlight any pair-programming experiences you have.
✨Discuss Real-World Applications
Prepare to talk about real-world AI challenges you've tackled in previous roles. This could include deploying and scaling ML models or contributing to research and prototyping projects.
✨Ask Insightful Questions
At the end of the interview, ask questions that show your curiosity about the company's projects and technologies. Inquire about their approach to machine learning and how they foster innovation within their teams.
