- UpvoteDownvoteShare Job
- Suggest Revision
Leverage modern ML/NLP methodologies (e.g., deep learning), computing hardware (e.g., GPUs), cloud infrastructure (AWS/Azure), open-source modeling frameworks (e.g., TensorFlow, Keras, PyTorch, XGBoost.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Job DescriptionJob DescriptionFocusKPI is looking for a NLP Data Scientist intern to work for our companys internal projects. We are building a state-of-the-art SaaS platform designed for business users to streamline their daily work and unlock new opportunities through AI.As an NLP Data Scientist, you will develop and refine our Large Language Models tailored for business applications.
InternExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
The Team: S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a ML Data Science team.
ExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
As a Data Science intern on our team, you'll be working on various algorithms and using Natural Language Processing (NLP) methods to work on some of our most interesting problems using expertly curated datasets.
InternExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Kensho is a Machine Learning (ML) and Natural Language Processing (NLP) company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Minimum of 3+ years of experience in data science with a focus on machine learning, deep learning, computer vision, NLP, and Spark. Leverage computer vision and NLP to enhance our product's ability to interpret and understand visual and textual data.
RemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
We are seeking a talented and skilled Machine Learning Scientist II to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better health care.
$110,500 - $180,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with Deep Learning, NLP, Transformers, and chatbot technology is a big plus. Skills: Data Science, Deep Learning, NLP, R Python etc. Experience with Deep Learning, NLP, Transformers, and chatbot technology is a big plus.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with Natural Language Processing (NLP), Large Language Models (IMs), and/or Recommendation Engines. Proficiency with data visualization tools (D3 js, R Shiny, Looker, Streamlit, or similar.
RemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Job Title:- Data Scientist (Remote - Boston, MA) Experience with neural networks, deep learning, and reinforcement learning, using frameworks such as TensorFlow. Build data science pipelines from feature generation, data visualization and models evaluation; design the solution, build initial code and provide documentation with ways of working to maximize time to value and re-usability.
RemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience building ML/NLP models in Azure Databricks and RStudio. This includes delivery of BI dashboards, ML models and Natural Language Processing (NLP) solutions to enable data science functions.
$147,200 - $229,925 a yearExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
As a Senior Data Scientist, you will collaborate with the Data Science and Machine Learning team and will create data science, machine learning, and Al solutions. Expertise in multivariate statistical modelling (e.g. clustering, regression, principal components and factor analysis, time-series forecasting, Bayesian methods) and machine learning (Random Forest, KNN, SVM, boosting and bagging, regularization etc.
RemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with cloud computing platforms and tools (AWS, GCP, or other). Identify trends and opportunities to drive innovation, both in what we do and how we do it; evaluate new data science, machine learning, and Al technologies and tools that can boost team performance, innovation and business value.
RemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Strong background in machine learning and deep learning, with practical experience in developing and deploying NLP models using frameworks such as TensorFlow, PyTorch, or similar. Develop and implement state-of-the-art NLP models using deep learning techniques, including recurrent neural networks (RNNs), transformer models (e.g., BERT, GPT), and sequence-to-sequence architectures.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Strong foundation in Machine Learning (ML), Deep Learning, LLMs and NLP. Develop AI-based systems for Natural Language Processing (NLP) Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow and similar related technologies.
ExpandApply NowActive JobUpdated Today
nlp job
FEATURED BLOG POSTS
Email Etiquette Principles - Why is it Important
Why is email etiquette important? Let's imagine you're hiring for a new role, and you’ve just received the email below.
10 Reasons HR is Important to an Organization
"Nothing we do is more important than hiring and developing people."
7 Importances of Organizational Culture and How to Build It
The world of work has drastically changed in the past few years. Where a good salary and a nice office might have been enough to attract talent in the past, employees today expect flexibility, growth opportunities, and a healthy work environment. In fact, 77% of applicants say they’d consider a company’s culture before applying for a job.
Collaborative Recruiting: The Key to a Better Talent Acquisition Strategy
Talent acquisition is a multi-stage process where candidates undergo various application steps before getting hired. The unfortunate reality is that it is a labor-intense system, with the hiring manager and recruiter often handling all of the work on their own. Ask any one of them, and you will hear about the overabundance of applications and the demanding task of filtering through them to find the best candidates. The quality of talent suffers under the weight of all that work on one person's hands. It's not easy, but as many companies are starting to realize, there is a better way. The future of talent acquisition lies in collaborative recruiting!
4 Talent Acquisition Trends Going Into 2023
For better or worse, a side effect of the COVID-19 pandemic was a marked shift in talent acquisition practices worldwide. With the struggle to retain talent that began in 2020, companies have had to rethink recruitment strategies. The result has been new talent acquisition trends that are well on their way to becoming commonplace. These are the practices that are going to become even more widespread going into 2023.
Why is Professionalism Important & How to Be Professional
You might have heard the word professionalism thrown around in the workplace, but do you know what it means? And do you know how to maintain professionalism no matter the circumstances?
Hiring Again After Mass Layoffs
It's never an easy decision to let members of your staff go, but depending on the state of your business, mass layoffs may have been the only way to survive. Now that you're months into the future, you may find yourself itching to start hiring again after previous layoffs.