at neo.tax
Full TimeJob Summary:
We are seeking a Senior Data Scientist with expertise in developing advanced ML and AI models. Familiarity with data science toolkits & libraries (e.g., PyTorch, Hugging Face, Langchain, SciKit Learn, Pandas, NumPy, Jupyter, etc.) is a plus, and bonus points if you've already played around with large language models (LLMs)! The ideal candidate will be responsible for designing, developing, and fine-tuning complex models that form a core component of Neo.Tax's current and future products.
P.S. We are a remote company, but we prefer to hire in time zones that can overlap with our HQ in Mountain View, CA!
Responsibilities:
• Design, develop, and maintain AI & LLM models to improve tax automation for Neo.Tax's customers.
• Establish methodologies and metrics for assessing and measuring the effectiveness of our predictive models in deployed environments.
• Collaborate with cross-functional teams—including engineers, product managers, and designers—to define and refine requirements for our AI & LLM models.
• Apply advanced statistical and machine learning techniques to extract insights from large datasets and cur high-quality training data.
• Conduct extensive research on emerging techniques and methodologies related to language modeling, and apply them to improve the performance of our models.
• Evaluate and fine-tune existing language models to address performance limitations, improve efficiency, and ensure continuous model enhancements.
• Stay up-to-date with the latest trends and advancements in AI and large language models.
Preferred Qualifications:
• Experience with the latest ML tools and libraries (e.g, Hugging Face Transformers, PyTorch, Langchain)
• Experience with data analysis and visualization tools
• Familiarity with prompt engineering and fine-tuning of LLMs
• Familiarity with the latest research on artificial intelligence, LLMs, and natural language processing
Requirements
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Statistics, Mathematics, or a related field
• Extensive experience in developing predictive models on a variety of tasks and domains, preferably with a proven track record of successfully deploying models in production environments
• Experience with statistical fundaments (e.g., regressions, properties of distributions, hypothesis testing, etc.)
• Experience with machine learning concepts, such as supervised vs. unsupervised learning, active learning, online learning, bagging, boosting, and online learning
• Experience with a variety of AI & ML models, such as decision trees, random forests, clustering methods, transformers, and large language models
• Strong grasp of Python, as well as the typical data science tool stack (e.g., Jupyter, Pandas, NumPy, SciKit Learn)
• Experience with SQL and data processing platforms (e.g., Spark, BigQuery, Snowflake)
• Strong problem-solving and analytical skills
• Excellent communication and collaboration skills
• Ability to work independently and as part of a team
Benefits
