Apply💸 130000.0 - 170000.0 USD per year
🔍 Software Development
- 2+ years of professional data engineering and/or machine learning experience.
- Significant experience with applied statistics and data modeling.
- Experience with SQL and relational databases.
- Experience building and owning production-level deep learning pipelines using real-world data, and deploying models for both real-time interactive use and batch processing.
- Strong Python programmer, and is familiar with standard software development tools and best practices, including cloud deployment, dependency management and versioning, and debugging cutting-edge libraries with incomplete documentation.
- Experience with NLP and training transformer ML models using PyTorch, or similar tools like TensorFlow/JAX.
- Experience with Agentic workflows, vector embeddings, and RAG systems.
- Familiar with cloud services, distributed systems, and other DevOps tools (Docker, Kubernetes, Terraform, etc.)
- Train, debug, and optimize deep learning runs on our GPU servers, and find new ways to increase model accuracy on both small and large datasets.
- Conduct deep learning experiments, do feature engineering, and contribute new ideas to improve our core data science approach.
- Work with a variety of datasets and survey results, clean and preprocess data, and figure out which models and loss functions are most appropriate for a given problem.
- Construct agentic workflows using off-the-shelf and custom fine-tuned LLMs.
- Augment agentic workflows with embedding databases.
- Deliver actionable guidance to important internal stakeholders, helping them understand nuances of the model output.
- Build subject matter context and think critically about what the data is saying, to understand what’s a real trend versus what’s a potential bug
Posted 27 days ago
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