Senior Software Engineer, Layer
Offers Equity
Metadata store for production ML
Be an early applicant
Metadata store for production ML
21-100 employees
Be an early applicant
Offers Equity
21-100 employees
Company mission
To serve as a collaboration-first metadata store that helps users build, train and track all their machine learning project metadata.
Role
Who you are
- Experience: 5+ years in fullstack development with Python and/or JavaScript/TypeScript
- Backend: Proficiency in FastAPI (or similar Python frameworks)
- Frontend: Strong React skills; experience with Material-UI (MUI)
- GraphQL: Hands-on experience building and maintaining GraphQL APIs
- Databases: Solid background in Postgres (or similar relational databases)
- Cloud: Hands-on deployment and scaling experience on GCP (or AWS/Azure)
- Containers: Proficiency with Docker and container orchestration
- Workflow Platforms: Familiarity with Temporal or similar tools
- Mindset: Product-focused, autonomous, and excited about building real-time systems and generative AI projects
- Don’t worry if you don’t meet every single requirement—if you’re enthusiastic and ready to learn, we’d love to hear from you
Desirable
- Experience in the gaming industry or developing tools for creative professionals
- Experience building real-time multiplayer features
- Personal interest or hands-on experience with Generative AI
- Background in developing administrative services (authorization, billing, etc.)
- Expertise in distributed systems or performance optimization
What the job involves
- We’re seeking a Senior Software Engineer to join our talented, ambitious team.
- You’ll design, develop, and deploy scalable systems that drive our generative AI platform.
- Working closely with our product and AI teams, you’ll build real-time interfaces and high-performance APIs that give our users a seamless experience
- Fullstack Development: Architect and implement features using Python (FastAPI) and React (MUI)
- API & Communication: Build and maintain GraphQL APIs to ensure efficient data flow between front-end and back-end
- Data & Infrastructure: Design and manage scalable data solutions using Postgres; deploy and manage infrastructure on GCP
- Containerization: Use Docker to containerize applications and manage deployments
- Workflow Orchestration: Integrate with Temporal (or similar) to handle complex workflows
Our take
Building, training and tracking machine learning data can be overwhelming and complex. Layer solves this problem by making it easier for users to log, display and compare their machine learning megadata sets.
With Layer, users can build, train, and track ML projects from a single platform, making collaboration and onboarding more streamlined for teams. Users can also access cloud resources if they need to boost their computing power. Companies like Neptune and ForePaaS already offer similar capabilities - but where Layer comes into its own, is that users can also easily share and search other public projects on the Layer platform, which has recently also gone open source.
This is an interesting move following the platform’s soft launch in early 2022, and perhaps indicates that Layer is looking now to position itself as something like the GitHub for ML teams. It may be a smart way for the company to distinguish itself from competitors - and certainly, there appear to be no obvious rivals so far.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
Company
Funding (last 2 of 3 rounds)
Nov 2023
$1.8m
SEED
Apr 2022
$5m
SEED
Total funding: $11.8m
Company benefits
- All-remote work style, work anywhere. Currently, we prefer teammates to be within UTC to UTC+5
- Equity plan
- Healthcare
- A budget to purchase your remote working setup
- Access for global co-working spaces
- $1000 L&D budget per year
- $40 social budget per month
- Company credit card
Company values
- 🚀 Execute Pragmatically: We approach work with speed and practicality in mind. We take individual ownership over our work, and we trust each other to deliver, but we avoid working in isolation. We strive to be excellent at what we do and will take time to deepen our knowledge of our craft; the more we learn, the better we can execute!
- 💓 Be Open: At Layer, openness applies to both the business and the people who work within it. We are continually open to giving and receiving feedback and learning new things from each other. We communicate openly and honestly. We are humble and kind and acknowledge that we are not always right
- 🌎 Think Global: we are committed to being not just a fully remote business but a fully global one. We want people worldwide to work with Layer and thrive as employees, partners, customers, and members of our community
Company HQ
City of London, London, UK
Articles
Leadership
Mehmet Ecevit
(CEO)Previously founded Oyun Studyosu, and co-founded Gram Games, serving as CEO of both companies.
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