At a Glance
- Tasks: Deploy ML models and collaborate with Data Engineers to solve real business challenges.
- Company: Deepstreamtech, a forward-thinking tech company in Greater London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Ideal for those passionate about continuous improvement and effective communication.
- Why this job: Join a dynamic team and make an impact with cutting-edge AI technologies.
- Qualifications: Strong Python skills and experience with MLOps tooling required.
The predicted salary is between 50000 - 65000 € per year.
Deepstreamtech is seeking a production-focused Machine Learning Engineer in Greater London. This role bridges the gap between data science and reliable software, with responsibilities including deploying ML models for business challenges and collaborating with Data Engineers to ensure continuous monitoring.
Ideal candidates will have strong Python skills, experience with MLOps tooling, and the ability to translate complex data insights for marketing and product stakeholders. A continuous improvement mindset and excellent communication skills are essential.
Production ML Engineer: GenAI, RAG & Scalable Models employer: Deepstreamtech
Deepstreamtech is an exceptional employer that fosters a culture of innovation and collaboration in the heart of Greater London. With a strong focus on employee growth, we offer continuous learning opportunities and a supportive environment where your contributions directly impact our cutting-edge projects. Join us to be part of a dynamic team that values creativity and encourages you to push the boundaries of technology while enjoying the vibrant lifestyle that London has to offer.
StudySmarter Expert Advice🤫
We think this is how you could land Production ML Engineer: GenAI, RAG & Scalable Models
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that highlight your Python prowess and MLOps experience. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and tools. Practice explaining complex data insights in simple terms, as communication is key in this role. We want to see how you can bridge the gap between tech and business!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Production ML Engineer: GenAI, RAG & Scalable Models
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your Python expertise in your application. We want to see how you've used it in real-world projects, especially in deploying ML models. Don't just say you're good at Python; show us what you've done with it!
Talk About Your MLOps Experience:If you've got experience with MLOps tooling, let us know! Share specific examples of how you've implemented these tools in your previous roles. This will help us understand how you can bridge the gap between data science and reliable software.
Communicate Clearly:Since this role involves translating complex data insights for various stakeholders, we need to see your communication skills shine through. Use clear and concise language in your application to demonstrate your ability to convey technical information effectively.
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 important updates. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Deepstreamtech
✨Know Your ML Models Inside Out
Make sure you can discuss the ML models you've worked with in detail. Be ready to explain how you deployed them, the challenges you faced, and how you overcame them. This shows your hands-on experience and problem-solving skills.
✨Brush Up on MLOps Tools
Familiarise yourself with the MLOps tools relevant to the role. Whether it's TensorFlow, Kubernetes, or any other tool, being able to discuss your experience with these will demonstrate your technical proficiency and readiness for the job.
✨Communicate Complex Ideas Simply
Practice explaining complex data insights in a way that non-technical stakeholders can understand. Use examples from your past experiences where you successfully communicated technical concepts to marketing or product teams.
✨Show Your Continuous Improvement Mindset
Be prepared to share examples of how you've sought feedback and made improvements in your work. This could be through refining models, optimising processes, or learning new skills. It highlights your proactive approach and commitment to growth.
