Senior Software Engineer, ML Platform
DailyPay · Remote · US-Remote · NYC Headquarters ·
COMPENSATION
$170k – $190k
Listed on the employer's job board (Ashby)
- Senior Software Engineer
- Fully remote
- Python, Scala, Go
- ML Platform Infrastructure
- AWS or GCP
You will design and build the infrastructure that supports every machine learning model at DailyPay, including feature engineering, training pipelines, and serving infrastructure. This software engineering role involves working with Python, Scala, and Go to create a self-service platform for data scientists, ensuring reproducibility and production safety at scale.
What you'll do
- Architect and build a unified ML platform for model development, deployment, and monitoring
- Design scalable services for feature generation, model training, and inference
- Create self-service tooling allowing data scientists to ship models independently
- Manage and optimize cloud infrastructure on AWS or GCP for cost and performance
- Build robust CI/CD pipelines for continuous integration and deployment of ML models
- Implement monitoring and alerting systems using tools like Datadog
- Lead technical design discussions and establish team norms for ML systems
- Mentor junior engineers and share domain knowledge to build technical depth
- Ensure security compliance and handle sensitive data according to company policy
What you'll need
- 5+ years of professional software engineering experience with production services
- Strong background in distributed systems, service-oriented architecture, and API design
- Proficiency in Python with a track record of writing maintainable, tested code
- Familiarity with ML frameworks such as scikit-learn, XGBoost, or PyTorch
- Experience with event streaming platforms like Apache Kafka
- Hands-on experience with infrastructure-as-code using Terraform or CloudFormation
- Solid CI/CD experience with GitHub Actions or equivalent tools
- Experience with containerization and orchestration using Docker and Kubernetes or ECS
- Proficiency in AWS, GCP, or Azure cloud platforms for ML workloads
- Experience with monitoring tools like Datadog, Prometheus, or Grafana
- Strong SQL skills and experience with data pipeline tooling like dbt or Snowflake
Nice to have
- Experience with experimentation infrastructure and A/B testing systems
- Background in fintech or other regulated industries
- Contributions to open-source infrastructure, platform, or MLOps projects
Stack
- Python
- Scala
- Go
- Terraform
- AWS SageMaker
- GCP Vertex AI
- Apache Kafka
- Docker
- Kubernetes
- Datadog
- SQL
- dbt
- Snowflake
How you'll work
- Fully remote position
- High-trust environment with significant autonomy
- Collaborative culture across data science and engineering teams