Risk ML Platform Software Engineer
4 weeks ago
At Square, we're building a platform that protects our customers and our business from fraud and payment disputes. Our Risk ML Platform is a critical part of this effort, and we're seeking an experienced software engineer to join our team.
What You'll DoYou'll work across the entire machine learning lifecycle, from training to deployment and model interpretability. You'll collaborate closely with internal customers to understand their needs and translate those into scalable software solutions.
Your Responsibilities- Develop a scalable AI platform that enables us to flag fraudulent activities.
- Work hand-in-hand with ML Modelers to identify and integrate new data sources, heuristics, and model types.
- Apply the latest theoretical advancements to enhance existing products, processes, and technologies, ensuring they remain at the forefront of the industry.
- Engage in the creation of experiments, prototyping, and architectural design, contributing to a diverse range of computer science domains such as machine learning, data mining, natural language processing, and performance analysis.
- 3+ years of experience in training and deploying ML models, developing ML software, and shipping customer-facing ML products.
- Deep understanding of modern ML techniques (e.g. Large Language Models) and the ML lifecycle from data gathering, training, model evaluation, MLOps, and productionizing models.
- Experience with large-scale distributed systems built around ML.
- Ability to produce production-quality code and services incorporating testing, evaluation, monitoring, and exquisite documentation, as well as the ability to quickly adapt to a new domain, hack MVPs, and iterate to improve the product.
- Experience using any of the major cloud vendors for high scale production use cases.
- Strong communication skills (verbal and written) with technical and non-technical stakeholders.
- Python, Java
- LightGBM/XGBoost, Onnx/PyTorch
- Kubernetes, AWS SageMaker, GCP Vertex
- Datadog, Sentry
- HTTP, JSON, gRPC, Protocol Buffers
- Kafka, event-driven microservice architecture.
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