- UpvoteDownvoteShare Job
- Suggest Revision
I have been working at Nutanix since May 2021, primarily on the machine learning algorithm side but also in areas like MLOPs lifecycle management, data preparation, and deployment.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
We are looking for 3 to 5 years of experienced Machine Learning Engineer with a strong background in data science, machine learning (ML), Natural Language Processing (NLP), and Large Language Models (LLM) technology.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Engineer, you will lead our data-driven initiatives, focusing on developing advanced ML models, leveraging NLP techniques, and utilizing LLM technology to extract actionable insights from our diverse data sets.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Engineer at TRM Labs, you will collaborate with an experienced team of engineers, data scientists, and research scientists to build scalable systems to detect, prevent, and mitigate cryptocurrency fraud and financial crime.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Distinct experience in advanced probability, statistics, machine learning, big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP. This role involves developing data science solutions, mentoring and imparting knowledge about machine learning and data concepts and techniques, as well as driving adoption of standards, processes, and tools to achieve high operational efficiency.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Data science, machine learning, optimization models, Master's degree 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.
$90,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
The Data Trust and Quality group is a Data Engineering team that focuses on maintaining our analytics tools and developing solutions to our data pipeline integrity and efficiency.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Including two-thirds of high school students and half of all college students in the US. Combining cognitive science and machine learning, Quizlet guides students through adaptive study activities to confidently reach their learning goals.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals. 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 Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
We're looking for a Machine Learning Engineer to join our Artificial Intelligence team and work with our team of data scientists to automate thetraining and evaluationofmodels within an Azure ecosystem.
Full-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Join our team as a Machine Learning Engineer, where you will play a pivotal role in leveraging data-driven solutions to drive innovation and business impact. Reporting to the Director of Data Science, you will collaborate with cross-functional teams to develop and deploy machine learning models that solve complex problems and drive actionable insights.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
This role requires a strong foundation in machine learning algorithms, hands-on experience in model development and deployment, and a passion for delivering measurable results through data-driven approaches.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Collaborate with data scientists and data engineers to explore and prepare data for machine learning applications, ensuring data quality and reliability.
Full-timeExpandApply NowActive JobUpdated Yesterday
machine learning data quality jobs Title: data engineer staff
FEATURED BLOG POSTS
10 Reasons to Be on Time at Work
Being punctual at work may not be something you’ve given much thought to, but it’s the foundation for building a successful career. All of your technical or job-specific skills will be in vain if your peers and superiors can’t trust you to show up on time and do the work. In fact, Simon Sinek once famously said that
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!