- UpvoteDownvoteShare Job
- Suggest Revision
Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals. Job title: Machine Learning Engineer. #Machine #Learning #Engineer.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
New York City (Hybrid On-Site): $161,900 - $184,800 for Senior Machine Learning Engineer. Senior Machine Learning Engineer. Youll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
ExpandApply NowActive JobUpdated Today - 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, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
We are a multidisciplinary team with expertise in machine learning, data engineering, and software development. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering.
Part-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML etc. San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer.
RemoteExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Proficiency in AI and machine learning concepts, programming languages (such as Python, Java, R), and AI frameworks (like TensorFlow, PyTorch). Position Summary – As an Artificial Intelligence Specialist you will employ a wide range of AI techniques, to include deep learning and machine learning, multi-agent systems, expert systems, and mixed-initiative human-machine teaming to enable outstanding intelligent collection and the exploitation of data from our collection systems.
Full-timeExpandApply NowActive JobUpdated 2 months ago - UpvoteDownvoteShare Job
- Suggest Revision
Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn. As a Junior Machine Learning Engineer, you will have the opportunity to work on exciting projects, develop your skills, and contribute to the development and implementation of machine learning solutions.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
ExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
- Suggest Revision
As a Senior Data Scientist, you will be responsible for developing advanced data science solutions leveraging machine learning and artificial intelligence to drive enterprise-wide innovation.
ExpandApply NowActive JobUpdated Today
FEATURED BLOG POSTS
5 Common Interview Mistakes
Everyone's interview process is unique in some form or fashion. Like most, your interview process is crafted so you can get the most information out of your candidates to increase hiring confidence and make the right hiring decisions. However, there are often small problems in interview processes that could ultimately affect the success of hiring decisions.
Job Rejection Email Response with Examples
Glassdoor estimates that, on average, there are about 250 applicants for every job vacancy out there. If you’ve ever applied for a job, the odds are that you’ve received the dreaded job rejection email.
Structured vs Unstructured Interviews
The goal of an interview is to evaluate candidates based on their skills, personality, and knowledge. You want to choose the BEST candidate from your candidate pool, so the interview is something you can't mess up. As you begin planning your interview process, one of the major decisions you'll face is whether the interview should be a structured vs unstructured interview. So let's take a dive into the differences and sort out which circumstances warrant which interview process.
How to Describe Your Personality with Examples
Imagine you’re in an elevator with the CEO of your dream company and you get to talking. The conversation is going well and you start to imagine yourself working for their company when the CEO turns around and asks you “tell me a bit about yourself.” Would this catch you off guard or would you be able to give a clear and succinct description of who you are?
4 Ways to Make Your Job Posting More Inclusive
According to a Glassdoor survey,
How to Calculate Net Income
Understanding your finances can be daunting even if you’re good with numbers. Your net income, in particular, is a key metric for determining how well you’re doing financially and whether your current way of operating is sustainable or not.
To ATS or not to ATS
As hiring is becoming more analytical and data-driven, companies have found ways to incorporate technology to help hire and recruit more efficiently. ATS, also known as an applicant tracking system, has become one of the most widely adopted technological recruiting tools to date. In fact, according to data from Capterra: