Machine Learning Research Scientist
GroupSolverLast month
- Where you can work from
- Remote — United States onlyUnited States
- Salary
- Salary not disclosedThe employer did not publish a range. We do not estimate one.
- Job type
- Part-time
- Experience
- Not stated
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Job description
GroupSolver is a market research tech startup based in San Diego with offices in Utah and Kosice, Slovak Republic. Combining AI and Crowd Intelligence, our technology helps decision makers and researchers find insights, which would otherwise remain hidden from traditional online surveys. Our clients include leading companies such as Google, Adidas, General Mills, Discovery, Lenovo, and Amazon.
- Research and development: work with and develop state-of-the-art NLP models to improve conventional market research practices.
Basic Qualifications
- MS/PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field.
- 2+ years of hands-on experience in predictive modeling, ML or large data analysis
- Algorithm and model development experience for large-scale applications
- Proficiency in at least one of the following languages: Python, R/Matlab, Java
- Comfortable working with teams in different time zones, (USA, Europe)
- Good communication skills, ability to explain technical concepts to non-technical audiences.
Preferred Qualifications
- Strong understanding of Transformer architecture and Attention mechanisms.
- 2 years of experience in NLP
- Familiarity with spaCy, AllenNLP, Gensim, Pytorch, Tensorflow, Deep Learning
- Knows the difference between RNN, CNN, LSTM, GANs.
- Familiar with Meta AI, Deepmind, Google AI, OpenAI and other big players.
Originally posted on Himalayas
Job availability & source
Still listed on the employer's own board at our last check, 10 hours ago
This job was originally posted by the employer or source shown below. We re-check the original listing regularly to keep its availability current, and send you straight to it to apply — we never sit in between.
- Source
- Himalayas
- Posted by the employer
- 22 Sept 2026
- First seen by us
- 22 Sept 2026
- Last checked
- 25 Oct 2026
via Himalayas — view on source
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