- UpvoteDownvoteShare Job
- Suggest Revision
The candidate should have subject matter expertise in designing and implementing machine learning pipelines including a deep understanding of core ML frameworks such as PyTorch, TensorFlow or Scikit-learn and 3rd party ML platforms from Palantir, Dataiku, DataRobot, Alteryx and other vendors.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics.
RemoteExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
- Suggest Revision
The ideal candidate will have a solid background in machine learning and statistical modeling, The Lead AI/ML Engineer will play a key role in developing and implementing data-driven strategies to improve lead generation and lead scoring, customer segmentation, and marketing automation activities.
$203,200 - $215,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
This may also include patent work related to image processing, databases, access management, natural language processing/understanding (NLP/NLU), and autonomous machines/vehicles.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Experience in natural language processing (NLP) and text analytics is highly desirable. Experience with statistics/machine learning packages like TensorFlow, Pytorch, Scipy, Keras, Numpy, Pandas, or Spark MLlib.
$107,000 - $162,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Research experience in machine learning, deep learning, and/or natural language processing. We are looking for strong engineers who have a background in generative AI and NLP, with experience in areas like language model evaluation; data processing for pre-training and fine-tuning; responsible LLMs; LLM alignment; reinforcement learning for language model tuning; efficient training and inference; and/or multilingual and multimodal modeling.
$85.1 - $251,000 a yearFull-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.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - 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.
$150Full-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Experience in distributed data processing systems (Hive, Redshift, Presto, Snowflake, etc) Craft and maintain data infrastructure with the Data Engineering team by translating business requirements from business partners to data models that will enable reporting, dashboards, and segmentation; responsible for data integrity.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Strong Technical Background: Proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, or SQL. Experience with data processing frameworks and tools like Apache Spark (including Databricks), and Hadoop and knowledge of database technologies like SQL databases (e.g., MySQL, PostgreSQL.
$150Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Design and develop advanced Machine Learning (ML) models to solve challenging problems related to natural language processing (NLP), recommendation systems, and predictive analytics.
$184,000 - $280,000 a yearFull-timeExpandUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Statistical analysis experience, including experimental design, regression modeling, and machine learning using tools such as GCP, Adobe analytics, Python, R, Spark SQL and MLlib for custom analysis, in conjunction with SQL for data query and extraction techniques.
$90,000 - $234,000 a yearFull-timeExpandUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Adapt data science algorithms (supervised and unsupervised learning, decision trees, neural networks, AI based image processing and feature extraction, Bayesian learning, etc) for modeling clinical trial data to support drug development.
$250Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
10 years full-time Software Engineering work experience, which includes 6+ years of software engineering experience in one or more of the following areas: advertising, recommendation systems, risk/fraud modeling, or natural language processing.
$216,000 - $378,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Knowledge in machine learning, artificial intelligence, statistical modeling, data visualization, and data analysis. Employ machine learning and statistical modeling to create and enhance data driven products.
$167,780 - $281,870 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago
machine learning natural language processing full time data engineering jobs in Daly City, CA
FEATURED BLOG POSTS
How to Prepare to Be Fired - What You Need to Do
If you’re reading this, let me be the first to tell you how sorry I am. Getting fired feels crappy, disheartening, hurtful, and all the other bad, sad words. But here’s what I want you to do. First, let yourself fumble for a minute. Then, pick your head up — sometimes getting fired is a blessing in disguise. If you think termination is around the corner, we’ll teach you how to prepare to be fired and what to do next so you land somewhere even better.
How to Find a Job That Makes You Happy - 11 Concerning Facts
Do you ever feel like your life is like one of those rom-com movie scene openers? You know, the ones where the main character rolls out of bed, awakened by a casually upbeat theme song, sulks their way to the coffee pot, and then trudges toward their computer to begin yet another boring day at work?
How to Decline a Job Offer You Already Accepted
When you think about it, turning down a job offer is not the worst position you could be in. If you’ve been lucky enough to consider multiple job offers, well, then you’re lucky enough.
How to Practice Fair Chance Hiring for People With Criminal Records
Usually when you think of your dream hire, you think of someone who is respectful, trustworthy, reliable, and has sound judgment, right? As you envision your ideal candidate with these qualities, the last person you think of is someone with a criminal record.
6 Common Mistakes to Avoid When Employer Branding
Currently, job searchers are putting extra effort into researching employers. The information they find plays a major role in whether they will pursue an opportunity with you or look for jobs elsewhere. That is why it is now more important than ever to be proactive and intentional when showcasing your workforce and workplace culture. Having a well crafted employer branding strategy can help you strategize and influence your potential candidates so they see your business in the best light. But in order to do that, you should be aware of some of the most common mistakes that employers make.
What to Say When Terminating an Employee
Terminating an employee is an inevitable part of doing business. Whether you’re re-structuring your department or you’ve identified a few employees who’re not living up to your expectations, letting people go is necessary for keeping your workforce healthy and thriving.
How to Utilize Keywords for Your Job Ads
Before we give you the scoop on how to utilize keywords in job ads, it would be helpful if we defined what keywords are and why they are important. In simple terms,