Highlights
Experience with LLM APIs, prompt engineering, vector databases, and knowledge graphs
Description
Job Summary
pWe are seeking a Data Scientist to develop and fine-tune models for Named Entity Recognition, text classification, semantic similarity, and clustering. You will work with pretrained embeddings and transformers to extract structured data from unstructured text. This role involves designing experiments to evaluate model performance and collaborating with product teams to deploy solutions into production.
Responsibilities
- Develop and fine-tune models for NER, text classification, semantic similarity, and clustering
- Work with pretrained embeddings, transformers, and LLMs to extract and normalize structured data from messy text
- Design and run experiments to evaluate model performance and guide improvements
- Collaborate with product and engineering teams to turn models into robust, production-ready solutions
- Explore research and open-source tools to improve performance and scalability
Required Skills
- Applied NLP and ML experience
- Strong Python coding skills
- Experience with Pandas, Scikit-learn, PyTorch or TensorFlow
- Familiarity with Spacy, HuggingFace Transformers, SBERT
- Understanding of embedding models and attention mechanisms
Required Skills Explained
- Hands-on experience in applied NLP and ML
- Strong coding skills in Python, and experience with Pandas, Scikit-learn, PyTorch or TensorFlow
- Familiarity with modern NLP toolkits such as Spacy, HuggingFace Transformers, SBERT, etc.
- Solid understanding of embedding models, attention mechanisms, and evaluation metrics
- Ability to break down abstract problems and build custom, data-driven solutions
Who is this for
pThis role is ideal for a Data Scientist who has hands-on experience in NLP and ML. You should be able to break down complex problems into actionable solutions and have a passion for continuously learning new tools and techniques.
Why This Job is a Good Opportunity
ulliTo be at the forefront of AI innovation in talent intelligenceliA chance to work with cutting-edge tools and techniques in NLP and MLliCollaborate closely with product and engineering teams to turn research into production solutionsliOpportunities for continuous learning and exploration through working on state-of-the-art projects
Interview Preparation Tips
- Prepare examples of your past NLP and ML projects, focusing on problem-solving and solution-building processes
- Be ready to discuss your experience with popular NLP toolkits and frameworks like Spacy and HuggingFace Transformers
- PRACTICE coding challenges related to NER, text classification, semantic similarity, and clustering in Python
- Understand the importance of model evaluation metrics and be able to explain them clearly
Career Growth in This Role
pThis role offers a path for growth both technically and strategically within the field of AI. As a Data Scientist, you can specialize further into specific areas of NLP or machine learning, or move towards leadership positions that involve managing teams and projects. The ability to build custom AI solutions also opens doors to more strategic roles in product development and innovation.pAdditionally, with a focus on robust and scalable systems, this role prepares individuals for senior-level data science and engineering roles where they can contribute to the overall architecture of large-scale applications.
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Skills
Frequently Asked Questions
What experience is required?Candidates should have hands-on experience in applied NLP and ML with strong coding skills in Python.
Can I apply if I don't have all the listed skills?Yes, we are open to candidates who can demonstrate relevant experience or a willingness to learn new tools.
What kind of research and open-source tools will I work with?You will explore LLM APIs, prompt engineering, vector databases, and contribute to open-source NLP projects.
