At a Glance
- Tasks: Build and maintain cutting-edge AI infrastructure for world-class machine learning products.
- Company: Join a dynamic tech company focused on innovation and collaboration.
- Benefits: Enjoy competitive pay, flexible hours, and opportunities for professional growth.
- Other info: Be part of a small, ambitious team with excellent career advancement potential.
- Why this job: Make a real impact by empowering over 100 Data Scientists and Engineers.
- Qualifications: Experience in Python or Go, containerisation, and Infrastructure-as-Code tools.
The predicted salary is between 60000 - 80000 € per year.
Requirements
- You are a Software Engineer who is passionate about building internal tools and takes pride in creating the foundational systems that enable others to excel.
- You understand the nuances of the machine learning product lifecycle and have a clear vision for how to move models efficiently from exploration to production.
- You possess modern systems programming skills in Python or Go, and you are comfortable selecting the best-fit technology for complex infrastructure challenges.
- You bring practical experience with containerisation and orchestration, specifically using Docker and Kubernetes to manage distributed systems at scale.
- You have a strong background in Infrastructure-as-Code (IaaC) using tools like Terraform or CloudFormation, combined with a deep interest in DevSecOps practices.
- You thrive in small, ambitious teams where you can take high levels of ownership and communicate effectively with both technical and non-technical peers.
- If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles.
What the job involves
- As a Software Engineer in the AI Platform team, you will be the architect of the infrastructure that makes world-class AI possible.
- Working closely with the Applied AI team, you’ll be building and maintaining the data science, MLOps, and deployment tooling that empowers our team of over 100 Data Scientists and Engineers.
- You will take ownership of the platform that enables us to transition from complex exploration to full-stack, production-grade machine learning products, ensuring our solutions are high-performing, scalable, and seamlessly integrated into diverse client environments.
- Taking ownership of our existing deployment and MLOps tooling to ensure our software delivery remains a significant lever for quality and reliability.
- Contributing to the continuous evolution of our technology stack, from building new features in our notebook development environments to refining model monitoring systems.
- Collaborating with a small, fast-moving team of customer-facing technologists to design and build the infrastructure our delivery teams need to succeed.
- Designing and implementing infrastructure-as-code and DevSecOps processes to support distributed, containerised microservices architectures.
- Integrating our core platform services across multiple cloud environments, including AWS, Azure, and GCP, to provide flexible solutions for our global clients.
- Scaling our internal enablement capabilities, acting as an entrepreneurial force that removes technical friction and accelerates the deployment of machine learning.
- We are open to conversations about part-time hours.
Software Engineer (Platform) employer: Deepstreamtech
Join a forward-thinking company that values innovation and collaboration, where as a Software Engineer, you will play a pivotal role in shaping the infrastructure for cutting-edge AI solutions. Our vibrant work culture fosters continuous learning and growth, offering ample opportunities to enhance your skills while working alongside a talented team of professionals. Located in a dynamic environment, we provide flexible working arrangements and a commitment to employee well-being, making us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer (Platform)
✨Tip Number 1
Network like a pro! Reach out to current employees at StudySmarter or in the industry on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! If you’ve got a GitHub or portfolio, make sure it’s up to date. Share projects that highlight your Python or Go expertise, especially those involving Docker, Kubernetes, or IaaC.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of the machine learning product lifecycle. Be ready to discuss how you can help transition models from exploration to production seamlessly.
✨Tip Number 4
Don’t hesitate to apply through our website! Even if you don’t tick every box, we value passion and potential. You might be the perfect fit for this role or another one that suits your strengths.
We think you need these skills to ace Software Engineer (Platform)
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for building internal tools shine through. We want to see how you take pride in creating systems that help others excel, so share your experiences and projects that reflect this passion.
Highlight Relevant Skills:Make sure to emphasise your modern systems programming skills, especially in Python or Go. If you've worked with containerisation tools like Docker and Kubernetes, or have experience with Infrastructure-as-Code using Terraform or CloudFormation, shout about it!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to match the job description. We love seeing candidates who understand the nuances of the machine learning product lifecycle and can articulate how they can contribute to our team.
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 this role or any other roles that might suit your strengths. Don’t hesitate – we’re excited to hear from you!
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, Go, Docker, and Kubernetes. Brush up on your Infrastructure-as-Code skills with Terraform or CloudFormation, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially those related to machine learning product lifecycles. Be ready to explain how you approached these problems and the impact of your solutions on the team or project.
✨Demonstrate Team Collaboration
Since this role involves working closely with both technical and non-technical peers, think of examples where you’ve successfully communicated complex ideas to diverse audiences. Highlight your experience in small teams and how you’ve taken ownership of projects.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI platform and its future direction. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially regarding innovation and collaboration.
