Conduct end-to-end analyses, wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
Mentor and guide junior engineers, fostering a culture of learning and technical excellence.
Work with large and complex textual and visual datasets.
Support the development and deployment of projects involving machine learned models for offline, batch-based data products as well as models deployed to online, real-time services.
Work in the contributor and visual intelligence team on text and visual understanding, along with fine tuning transformer models to derive embeddings for multiple input types.
Productionize and automate model pipelines within Python services.
Drive and advocate adoption of best practices in ML development and operations, and mentor newer engineers in those practices.

Requirements

Experience developing and productionizing machine learning models, particularly in neural networks, computer vision and LLMs including their supported data pipelines.
Experience with machine learning using packages such as PyTorch, TensorFlow, Spark MLlib, XGBoost, and Sklearn.
Strong coding skills in Python or equivalent (Java, C++).
Solid understanding of engineering and infrastructure best practices.
The curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal.
We highly value experience of working with LLMs, utilizing LLM APIs (OpenAI, Bedrock, etc), prompt engineering and evaluation.
A Bachelor’s Degree or an equivalent work experience is required

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonmachine learningneural networkscomputer visionLLMsPyTorchTensorFlowSpark MLlibXGBoost

Soft Skills

mentoringtechnical excellencecuriositypersistence