- UpvoteDownvoteShare Job
- Suggest Revision
Expertise in a subset of the following: machine learning, object detection, image segmentation, computer vision, image processing, remote sensing, spectral science, neural models for autonomous vehicles/robotics, structure from motion (SfM), natural language processing (NLP), large language models, data fusion, change detection, and pattern of life analysis.
$229,000 a yearFull-timeExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Proven understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
FM Global is seeking a Machine Learning Operations Data Engineer II to join our AI/ML team to support Machine Learning Engineering, working very closely with Data Science, Data Engineering, Subject Matter Experts and Solution Architecture teams.
$127,100 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Design and implement natural language processing (NLP) and natural language understanding (NLU) systems to enhance chatbot interactions. Develop strategies for continuous improvement of chatbot performance through machine learning and user feedback.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Apply cutting-edge machine learning algorithms, including but not limited to deep learning, ensemble methods, and natural language processing, to analyze large-scale datasets related to customer behavior, product attributes, and digital commerce performance.
$260,800 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$216,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with multi-modal data specification and requirements, data annotation and natural language processing. As a Data Annotation Program Manager, you will interact with our US-based Science and Data team on data objectives and participate in the operational planning to achieve these objectives with resources based in India.
$142,800 a yearFull-timeExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
- Suggest Revision
5+ years of practical experience in building, evaluating, scaling, and deploying machine learning pipelines with Python, preferably within the AWS ecosystem. Experience in assessing and implementing new data tools to enhance the machine learning stack.
$235,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Proficiency in Python, Pandas, Databricks, JavaScript, or other scripting languages for data processing and automation. 2 years of experience with Data Pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS, or Python.
Full-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
100% REMOTE Senior ML Ops Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company! Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, PyTorch, Tensorflow/Keras, MLlib, etc.
$235,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Senior Machine Learning Operations Engineer. Ability to design, train, and evaluate machine learning and AI models while adhering to best practices including model selection, validation, bias/variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc.
$235,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
$172,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Collaborate with data scientists and machine learning engineers to evaluate and improve large language models. Stay up-to-date with the latest research in data engineering, web scraping, and machine learning; actively participate in research discussions and reading groups.
$58.59 an hourFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
Full-timeExpandApply NowActive JobUpdated Today
machine learning natural language processing python r data jobs Title: data science manager
FEATURED BLOG POSTS
Recruiting in a Recession: Hard Truths That Talent Acquisition Experts Must Accept
The summer had economists from around the globe embroiled in a debate about a possible recession coming in the next few years (or months). As of October 2022, the U.S. Labor Department data put the current inflation rate at 7.7%. The recent layoffs in the tech industry are just the first of what is soon to be a string of cutbacks by companies looking to save costs. For recruiters, this means freezes in hiring and fewer openings. It will also include the uphill task of finding the best candidates for them from the coming influx of recently laid-off job seekers. Now is probably a good time to brace for tough times in the next few years in the talent acquisition industry. To survive and thrive recruiting in a recession, here are some hard truths you will need to accept.
10 Importancies of Setting Realistic Goals
We’ve all heard how important it is to set professional and personal goals. Developing and establishing goals keeps us motivated and moving forward in life. But not all goals are created equal. If you’re chasing goals that are too lofty, you’ll end up disappointed when you cannot reach them. Setting goals that are achievable and measurable is the key to success.
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.