Responsibilities
:
1. Take stock of any existing code base, work on consolidation and streamlining of repositories and propose an internal technical roadmap.
2. Work closely with our investment stakeholders and quantitative researcher to maintain alignment with their requirements.
3. Build and maintain scalable, tested, production grade systems and infrastructure for containerization, deployment, versioning, testing and monitoring of ML models
4. Take full ownership of the products you and your team work on to ensure continued support and improvements.
5. Support and troubleshoot live production systems.
6. Willingness to pick up and learn new software, ML technologies and tools used by data scientists.
Requirements:
7. Bachelor’s degree inputer Science, Engineering, or related subject
8. Minimum of 2 years of fulltime software development experience
9. Experience with highly available distributed systems and working with large datasets
10. Proficiency in Python and Java
11. Kubernetes and Cloud (AWS or GCP) experience
12. Experience working in a Linux environment, using version control
Nice to have:
13. Exposure to any of the following: Kotlin, Rust, SLURM, PostgreSQL
14. Basic knowledge of financial markets
15. Experience with gRPC, Apache Arrow
16. Experience with ML frameworks such as PyTorch and TensorFlow
17. Experience with ML infrastructure frameworks like Kubeflow, MLFlow etc
18. Basic knowledge of financial markets