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- Tasks: Lead the development of high-performance APIs for machine learning models.
- Company: Join a stealth-mode deep tech startup revolutionising AI model training and scaling.
- Benefits: Enjoy equity options, autonomy, and a fast growth path in a no-ego team.
- Why this job: Work at the forefront of ML systems with a close-knit, innovative team.
- Qualifications: 5+ years in software engineering with strong backend and cloud-native skills required.
- Other info: Experience with Kubernetes, Terraform, and ML deployment is essential.
The predicted salary is between 36000 - 60000 £ per year.
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Senior Software Engineer – API & ML Infrastructure, London
Client: SoCode
Location: London, United Kingdom
Job Category: Other
EU work permit required: Yes
Job Reference:
ea490a1f1707
Job Views:
4
Posted:
29.06.2025
Expiry Date:
13.08.2025
Job Description:
About Us
We’re a stealth-mode deep tech startup rethinking how AI models train, adapt, and scale. Our mission is to optimise large-scale AI systems — making them faster, smarter, greener, and cheaper. If you’re excited by infrastructure that powers the frontier of machine learning, we’d love to talk.
The Role
We’re looking for a Senior Software Engineer to lead development of a high-performance API platform that serves machine learning models at scale. You’ll take full ownership of the infra stack — from backend APIs to deployment and scaling. This role sits at the intersection of MLOps, cloud-native architecture, and distributed systems.
What You’ll Do
- Build scalable APIs with FastAPI (or similar), Python, and modern web tooling
- Design and maintain ML model serving infrastructure
- Collaborate with ML engineers on training and deployment workflows
- Own deployment: Kubernetes, Terraform, CI/CD pipelines
- Build a slick analytics frontend using React or similar
- Drive best practices in system design, performance, and reliability
What We’re Looking For
- 5+ years of software engineering experience
- Strong backend skills — Python, REST APIs, FastAPI
- Proven experience scaling cloud-native systems (AWS, microservices, IaC)
- Kubernetes + Terraform expertise in production environments
- Solid understanding of ML deployment (e.g. PyTorch, TensorFlow, JAX)
- Frontend skills with React/TypeScript or similar
- Bonus: big data / real-time analytics / multi-cloud
Why Join?
- Equity with serious upside and rapidly rising valuation — early-stage, high-impact
- Work at the cutting edge of ML systems and optimisation
- Autonomy and ownership from day one
- Fast growth path — help define both tech and culture
- Close-knit, no-ego team of engineers and researchers
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Senior Software Engineer – API & ML Infrastructure employer: SoCode
Contact Detail:
SoCode Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software Engineer – API & ML Infrastructure
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as FastAPI, Kubernetes, and Terraform. Having hands-on experience or projects showcasing these skills can set you apart during discussions.
✨Tip Number 2
Network with professionals in the AI and machine learning space, especially those who have experience in MLOps and cloud-native architecture. Engaging in relevant online communities or attending meetups can help you gain insights and potentially get referrals.
✨Tip Number 3
Prepare to discuss your previous experiences with scaling cloud-native systems and deploying ML models. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will demonstrate your problem-solving abilities.
✨Tip Number 4
Showcase your passion for optimising AI systems by staying updated on the latest trends and advancements in the field. Mentioning recent developments or innovations during your conversation can highlight your enthusiasm and commitment to the role.
We think you need these skills to ace Senior Software Engineer – API & ML Infrastructure
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in software engineering, particularly with Python, REST APIs, and cloud-native systems. Emphasise any work you've done with Kubernetes, Terraform, and machine learning deployment.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's mission. Mention specific projects or experiences that align with building scalable APIs and working with ML infrastructure.
Showcase Your Technical Skills: Include a section in your application that showcases your technical skills. List your proficiency in tools like FastAPI, React, and any experience with big data or real-time analytics, as these are relevant to the position.
Highlight Collaboration Experience: Since the role involves collaboration with ML engineers, mention any past experiences where you worked in cross-functional teams. This will demonstrate your ability to communicate and work effectively with others in a tech environment.
How to prepare for a job interview at SoCode
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, REST APIs, and FastAPI in detail. Bring examples of projects where you've built scalable APIs or worked with cloud-native systems, as this will demonstrate your technical expertise.
✨Understand the Company’s Mission
Research the startup's mission to optimise AI systems. Be ready to explain how your skills and experiences align with their goals, particularly in MLOps and distributed systems, to show that you're genuinely interested in their work.
✨Prepare for System Design Questions
Expect questions about system design, performance, and reliability. Think through how you would approach building a high-performance API platform and be ready to discuss your thought process and best practices.
✨Demonstrate Collaboration Skills
Since the role involves working closely with ML engineers, be prepared to discuss your experience collaborating on training and deployment workflows. Highlight any past teamwork experiences that showcase your ability to communicate effectively and drive projects forward.
