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Senior Applied Scientist - NLP
Black Ore
WorldwideRemote10mo ago
- Employment
- Full-time
- Seniority
- Senior
About the role
- Owner Mentality - Desire to take initiative, identify problems and implement solutions
- Mission Driven - Passion for building AI/ML solutions that reimagine how businesses and consumers operate
- Intellectually Curious - Excitement going deep and building detailed understanding of the function, role, customer and problem space
- Team Oriented - Ability to collaborate respectfully and put the team above the self
- Research and engineer NLP solutions to solve real-world problems within the tax industry and push state of the art LLMs and assistants.
- Independently design and implement algorithms, train state of the art large language models (LLM) on large data, and evaluate their performance.
- Drive engineering and science that can be applied to Black Ore platform development
- Fine tune models
- Masters degree in Computer Science, Computer Engineering, Artificial Intelligence or relevant technical field, or equivalent practical experience. PhD preferred but not required.
- Applied Research experience in one or more of these areas: NLP, NLU, machine learning, deep learning, or related fields.
- Direct experience in Summarization, Classification and/or Extraction
- Experience with NER (named-entity recognition)
- End to end experience delivering production-ready code
- 3+ years of experience with development and implementation of LLM algorithm/systems and model training.
- Direct experience in generative AI and LLM's, and implementing solutions to production
- Experience working with machine learning libraries like Pytorch.
- Familiar with scripting languages such as Python and shell scripts.
- Direct experience in Prompt Engineering
- Continued interest in LLM trends and the latest in cutting edge models within AI
- Proficient in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, or similar
- Strong understanding of ML fundamentals, including supervised/unsupervised learning, model evaluation, feature engineering, and overfitting/underfitting
- Experience working with large datasets and building production-ready data pipelines
- Competitive salary and equity based compensation
- Employer-paid medical, dental and vision insurance
- Ability to define your own success
- Continuous learning and new challenges to master
Perks & benefits
- Vision Insurance
- Equity Compensation
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