At a Glance
- Tasks: Deploy ML models and collaborate with Data Engineers to solve real business challenges.
- Company: Join Deepstreamtech, a forward-thinking company in Greater London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Ideal for those with a continuous improvement mindset and excellent communication skills.
- Why this job: Make an impact by bridging data science and software engineering in a dynamic environment.
- Qualifications: Strong Python skills and experience with MLOps tooling required.
The predicted salary is between 60000 - 80000 € 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
- 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 in London employer: Deepstreamtech
Deepstreamtech is an exceptional employer that fosters a dynamic work culture in Greater London, where innovation and collaboration thrive. Employees benefit from continuous professional development opportunities, a supportive environment that encourages creativity, and the chance to work on cutting-edge projects in machine learning. With a focus on employee well-being and a commitment to impactful work, Deepstreamtech stands out as a rewarding place for those looking to make a difference in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Production ML Engineer: GenAI, RAG & Scalable Models in London
✨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 your communication skills. Practice explaining complex data insights in simple terms, as this is key for collaborating with marketing and product teams. We want to see you shine!
✨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 take the initiative to engage directly with us.
We think you need these skills to ace Production ML Engineer: GenAI, RAG & Scalable Models in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your Python skills and any experience with MLOps tooling. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about bridging data science and software. We love seeing candidates who can communicate complex ideas clearly, so show us your communication skills here.
Showcase Continuous Improvement:In your application, mention any instances where you've implemented improvements in your previous roles. We value a continuous improvement mindset, so share examples of how you’ve made processes better or more efficient.
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’re considered for the role. Plus, it shows you’re keen on joining our 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 those challenges. 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, be prepared to discuss how you've used these in past projects. This 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. This will highlight your communication skills.
✨Show Your Continuous Improvement Mindset
Be ready to share examples of how you've sought feedback and made improvements in your work. Discuss any initiatives you've taken to enhance processes or outcomes in your previous roles. This will reflect your proactive attitude and commitment to growth.
