QOVES

About QOVES
QOVES is a technology company pioneering facial aesthetics, helping consumers make smarter beauty decisions. Every day, people make important decisions about their appearance based on guesswork or generic advice. We help them decide with clarity instead. Our platform gives customers a clear, science-backed understanding of their face, paired with bespoke advice on how they can look better. Our work reaches millions: more than 2.5 million people follow QOVES across platforms and most importantly, our customers are delighted, with 4.8 stars across 600+ reviews; we believe this reflects the care and sensitivity with which we approach everyone who comes to us for guidance. We're a profitable, growing company headquartered in London, with a team across the globe. What guides us is simple: people deserve more than one-size-fits-all advice when it comes to their appearance. Every decision we make (from the science behind our models to the way we communicate results) is grounded in evidence, responsibility, and a broad, inclusive understanding of beauty.

About the Role
You will join the backend team building the computer vision and machine learning systems that power QOVES's facial analysis platform. The non-negotiable is proven production experience: at least 3 years building scalable software in Python, with hands-on work shipping AI or ML features, including computer vision or LLM-based systems, into a live codebase. You will work closely with the AI Research team to translate research prototypes into production-ready code, own delivery end to end across analysis, design, coding, testing, deployment, and support, and optimise applications for performance and scalability as usage grows. You will also work with the wider team to spot problems early and resolve them before they become blockers.

What We're Looking For
• 3+ years of professional experience in production-level scalable software development with Python
• Strong proficiency with Python for building production-grade APIs
• Hands-on experience integrating AI or ML features, including computer vision or LLM-based systems
• Solid grasp of software architecture principles and API design, with the ability to contribute meaningfully to architectural decisions
• Experience owning work across the full software development lifecycle
• Strong sense of code quality, testing discipline, and engineering best practices
• Excellent communication skills, with the ability to articulate trade-offs and design decisions clearly
• A collaborative, proactive mindset with strong problem-solving skills

Nice to Have
• Knowledge of MLOps practices and experience with Data Version Control (DVC) or similar tools
• Knowledge of data pipelines, including designing production-grade GPU inference pipelines for high-throughput workloads
• Exposure to frontend or full-stack development
• Experience working in a startup or fast-paced product environment
• Experience building data pipelines or working with large-scale data processing

Why Join
• Build the computer vision and machine learning systems behind a product used by millions
• Fully remote with real autonomy and direct collaboration with the AI Research team
• A profitable, growing company with a global team

Compensation and Logistics
• Remote, full-time, open to applicants worldwide
• Compensation competitive, based on experience

We make software that helps patients and cosmetic medical clinics diagnose, plan, and visualize appearance improvements. Our platform is used by clinics worldwide with an online fan base of 2 million+ and quickly growing.

Unlike typical cloud-only startups, we've built a cost-optimized hybrid infrastructure that combines AWS CDN delivery, bare metal compute, Kubernetes clusters, and self-hosted internal tools, saving significantly on compute while maintaining enterprise-grade security and performance.

About the Role

We're looking for a Senior DevOps Engineer to establish and lead our DevOps culture from the ground up. This isn't just about maintaining infrastructure, you'll be setting company-wide policy, building security-hardened environments, and creating the documentation and processes that will scale with us.

In short, you will be guiding the technical team on how to ensure our Production systems stay robustly online to serve our many customers.

What You'll Build

• Hybrid Infrastructure Management: Architect and maintain our unique infrastructure spanning AWS CDN, bare metal servers, and Kubernetes clusters for computationally intensive facial analysis workloads
• CI/CD Pipeline Architecture: Design and implement CircleCI or Jenkins pipelines with comprehensive build testing, versioning, and change logging
• Zero-Trust Networking: Build and maintain mesh topology networks using Tailscale or Wireguard to securely connect our hybrid infrastructure
• Security-First Culture: Establish and enforce security policies including key rotation, access controls, compliance frameworks, and employee security management
• Infrastructure as Code: Document and codify all infrastructure decisions, creating repeatable, auditable deployments
• Containerization Strategy: Implement and optimize Docker/K8s deployments for our AI/ML workloads
• Cost Optimization: Continue our approach of strategic compute placement using owned, rented or borrowed infrastructure where it makes financial sense without sacrificing security or reliability
• Observability & Monitoring: Implement comprehensive logging, monitoring, and alerting across our distributed systems

What You Bring

• 5+ years of DevOps or infrastructure engineering experience, with a track record of building from scratch
• Hybrid infrastructure expertise: Experience managing both cloud (AWS) and self-hosted infrastructure, understanding the tradeoffs and security risks of each
• Kubernetes production experience: Deep knowledge of K8s cluster design, operations, and scaling
• Networking mastery: Strong understanding of VPCs, mesh networks, VPNs, and zero-trust architectures (Tailscale, Wireguard, or similar)
• Security-first mindset: Experience with security compliance, key management, IAM policies, and hardening production systems
• CI/CD expertise: Hands-on experience building robust pipelines (CircleCI, Jenkins, GitHub Actions, or similar) for build testing before deployment
• Infrastructure as Code: Proficiency with Terraform, Ansible, or similar tools
• Scripting & automation: Strong Python, Bash, or Go skills for tooling and automation
• Policy & documentation: Ability to establish best practices and document them clearly for team adoption
• Leadership mentality: Comfortable setting standards and directing technical decisions, not just executing them

Technologies We Use

• Cloud: AWS (CDN, S3, IAM)
• Compute: Bare metal servers, Kubernetes (transitioning from bare metal)
• Networking: Tailscale/Wireguard for mesh topology, zero-trust architecture
• CI/CD: CircleCI or Jenkins
• Containerization: Docker, Kubernetes
• IaC: Terraform
• Monitoring: Grafana, Sentry, Glance

Why QOVES?

• Ownership & Impact: You'll establish the DevOps foundation and policy that scales with the company.
• Profitable & Growing: We're VC-backed and profitable, meaning sustainable growth and job security
• Real-World AI: Work on infrastructure powering actual AI/ML workloads used by medical professionals worldwide
• Security Focus: Build a security-hardened culture from day one, not retrofit it later
• Small Team, Big Decisions: Your architectural choices will shape how we scale to the next level

What Success Looks Like

• You've audited our current infrastructure, documented everything, and established a roadmap
• CI/CD pipelines are running, security policies are enforced, and zero-trust networking is operational
• The team is following your documented standards, infrastructure is code, and we're scaling confidently

Compensation

Competitive salary based on experience