Apply📍 United States, Mexico, United Kingdom, Australia, Japan, India, Philippines
🧭 Full-Time
🔍 Education
- Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus.
- A strong understanding of the math and theory behind machine learning and deep learning.
- Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).
- Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).
- An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.
- Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.
- Excellent communication and teamwork skills.
- Fluent in written and spoken English.
- Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered.
- Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices.
- Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.
- Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters.
- Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs.
- Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings.
- Optimize models for scaled production usage.
- Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners.
- Write clean, efficient, and modular code, with automated tests and appropriate documentation.
- Stay up to date with technology, make good technological choices, and be able to explain them to the organization.
AWSBackend DevelopmentDockerPythonSoftware DevelopmentSQLData AnalysisGitMachine LearningNumpyPyTorchAlgorithmsData scienceData StructuresCommunication SkillsAnalytical SkillsCI/CDProblem SolvingRESTful APIsDocumentationExcellent communication skillsJSONScripting
Posted 9 days ago
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