Drweng
Data Developer
Montreal
Sponsorship not specifiedDetected 23 days ago
PythonVector DatabasesDockerMachine LearningSparkAirflowData EngineeringLLMsRAGResearch
About the role
- DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world.
- Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets.
Responsibilities
- Design and build data pipelines for RAG systems, including document ingestion, chunking, embedding generation, and vector storage.
- Build ingestion pipelines for structured and unstructured data sources into a centralized data lake, ensuring data is clean, normalized, and accessible for analytics, research, and AI workloads.
- Develop data processing workflows to prepare and optimize datasets for fine-tuning and inference workloads.
- Build monitoring and evaluation frameworks to measure retrieval quality, latency, and system performance.
- Collaborate with ML engineers to optimize data formats and storage patterns for GPU-accelerated inference.
- Implement caching strategies and data versioning systems to support efficient model serving.
- Deploy and manage vector databases, embedding services, and data processing pipelines.
- Drive initiatives to improve data quality, reduce latency, and enhance the accuracy of retrieval systems.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
- Strong experience with RAG architectures, including vector databases (Milvus, ChromaDB, Pinecone, Weaviate, or Qdrant).
- Proficiency in Python with experience using DAG-based orchestration platforms (Airflow, Dagster, Prefect, or similar).
- Hands-on experience with embedding models and semantic search systems.
- Experience with distributed data processing frameworks (Apache Spark, Ray, or Dask).
- Familiarity with Docker, containerization, and orchestration platforms.
- We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.
This listing is sourced directly from Drweng's careers page and normalized into a canonical job model.