Machine Learning Engineer
Swish Analytics Inc. · San Francisco, CA, United States ·
COMPENSATION
€•• – ••k
Listed on WeAreDevelopers
- Fully remote (EU)
- Python + Rust
- Kubernetes & CI/CD
- Sports betting domain
- Senior level
You will design and implement systems that generate accurate sports datasets and predictions with minimal latency. The role requires close collaboration with DevOps and Data Engineering teams to scale workloads on Kubernetes and maintain cloud-native data solutions.
What you'll do
- Design and optimize systems for high-accuracy, low-latency sports predictions
- Evaluate internal tools to improve data scientist modeling workflows
- Build, test, deploy, and maintain production-grade software components
- Collaborate with DevOps to scale workloads on Kubernetes using automation
- Support maintenance of cloud-native EDW and ETL solutions
- Promote best practices for deployment, documentation, and coding standards
- Develop database structures aligned with overall system architecture
What you'll need
- Master’s degree in Computer Science, Math, Data Science, or related field
- 5+ years of experience delivering clean, efficient production code
- Proven background in quantitative analytics, trading, or engineering
- Experience developing data science modeling systems at scale
- Proficiency in Python and modern machine learning frameworks
- Strong SQL skills with specific experience in MySQL
- Ability to communicate technical concepts to diverse audiences
Nice to have
- Background or interest in Rust programming language
- Experience with large-scale data processing techniques
Stack
- Python
- Rust
- SQL
- MySQL
- Tensorflow
- Kubernetes
- ETL
- CI/CD