Senior Software Engineer – MLOps Framework
Senior Software Engineer – MLOps Framework
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Senior Software Engineer – MLOps Framework
Help Build the Backbone of an Open-Source and SaaS MLOps Platform
Our client is on a mission to streamline the way ML engineers build production-ready pipelines. They are looking for an experienced Senior Software Engineer to join the core team and help shape the future of their open-source framework and commercial SaaS product.
This role is ideal for someone with deep Python expertise, a passion for clean API design, and an understanding of cloud-native environments. You'll work at the intersection of open-source development, production-grade infrastructure, and user-centric design, helping data scientists and ML engineers deploy and manage scalable ML pipelines with confidence.
What You’ll Do
* Core Framework Development: Own the design and implementation of the MLOps framework internals in Python, making key architectural decisions.
* SaaS Feature Development: Build and enhance enterprise-grade features on AWS.
* API Design: Develop intuitive, well-documented FastAPI-based APIs that power the platform.
* Cloud & Infrastructure Awareness: Ensure services run smoothly in containerized environments (Docker, Kubernetes).
* Support & Enablement: Assist the open-source community and help commercial customers onboard and thrive.
* Collaborate Across Teams: Work closely with product to influence roadmap and with engineering to maintain code quality.
* Champion Best Practices: Uphold high standards through testing, code reviews, and strong documentation.
Tech Stack You’ll Work With
* Languages & Frameworks: Python, FastAPI, SQLAlchemy, Pydantic
* Testing & CI/CD: Pytest, linting tools, CI/CD pipelines
* ML Integration: Hugging Face, TensorFlow, PyTorch, and other MLOps tools
What We’re Looking For
* Python Expertise: 6+ years of hands-on experience building production-level Python applications.
* API Craftsmanship: Proven ability to build RESTful APIs, preferably with FastAPI.
* MLOps & Pipeline Fluency: Understanding of ML development workflows and MLOps challenges.
* Architecture Know-how: Ability to design clean, extensible, and maintainable systems.
* Cloud-Savvy: Solid grasp of containerization and cloud infrastructure (Docker, Kubernetes, AWS).
* Testing Champion: Comfortable with test-driven development and automated test coverage.
* Clear Communicator: Able to explain technical concepts clearly and collaborate effectively.
* Bonus Points: Experience deploying MLOps infra with tools like Terraform or Helm on GCP, Azure, or AWS.
Seniority level
* Seniority level
Mid-Senior level
Employment type
* Employment type
Full-time
Job function
* Industries
Technology, Information and Media, Computer and Network Security, and Research Services
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