- UpvoteDownvoteShare Job
- Suggest Revision
6+ years of experience in machine learning, data analysis, or a related field. Strong knowledge of machine learning algorithms and data analysis techniques. Identity: Using machine learning methods and systems, this team reduces the prevalence of inauthentic identities in Cash’s ecosystem, provides a first line of defense against bad actors attempting to circumvent our IDV controls while simultaneously building our confidence in existing and new customers' identities.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
The Machine Learning Engineer sits on the Commercial Data Science (CDS)Team within our Strategic Analytics & Intelligence Organization (SAI) and exists to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data quicker and more effectively.
$165,200 - $306,800 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Utilizes eDiscovery review platforms including Relativity, Recommind and other analytics tools including TAR, predictive coding, and Early Case Assessment; strong use and familiarity in handling data processing and document processing.
$150,000 - $165,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink. Data Processing Frameworks: Implement and optimize data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
$170,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Plus Power is looking for a driven Software Engineering Manager to lead our team developing Plus Power's real time energy trading platform. The ideal candidate would work under the Head of Analytics in collaboration with the leads of the Machine Learning, Optimization and Product Management teams to scale the product to handle our growing fleet of energy storage assets.
$250Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, Databricks, EMR. 6+ years' experience in engineering data pipelines using big data technologies (Spark, Flink etc.
Full-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Turn unstructured data into useful information through natural language processing methods and other related approaches. 8 years' experience in application development including machine learning engineer, data scientist, data analyst or analytics engineer.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
By applying advanced machine learning techniques to recent breakthroughs in genomic science, Freenome is developing simple blood tests to detect early-stage cancer and make treatments more effective.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Create strategies and blueprints that use machine learning to improve operations and refine processes (across finance operations, including record-to-report, procure-to-pay, order-to-cash.
$131,100 - $336,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Working knowledge on data science & machine learning, data exploration, and visualization via Python is a plus. Partner with data engineering to define requirements for data pipelines and warehouse (Snowflake) data models.
$90,000 - $127,000 a yearFull-timeExpandApply NowActive JobUpdated Today - 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.
$196,800 - $260,800 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Our rapidly growing Industrial market encompasses a a broad range of projects that can span from Water/Wastewater treatment, Food & Beverage processing, Mineral Processing, Renewable Fuels, Pulp and Paper, Steel & Aluminum, Specialty chemical, Industrial Energy, Manufacturing, Automotive and Emerging Industrial Markets like EVBattery, Data Centers and Semiconductors.
$80,000 - $110,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
By integrating this data with our online systems, we empower multiple business lines, drive critical machine learning models, and fuel fast-paced experimentation. Bonus if those were open-sourced big data processing frameworks using technologies like Spark, Airflow, Kafka, Flink, Iceberg, Deltalake.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day.
$161,000 - $239,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
As a technical leader you will lead the vision and strategy to build foundational and critical data models which are highly leveraged across SoFi for analytical, reporting, and machine learning use-cases.
$144,000 - $247,500 a yearFull-timeExpandUpdated 4 days ago
machine learning natural language processing time data engineering jobs in San Francisco, CA
FEATURED BLOG POSTS
Virtual Reality Job Interviews
With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
A Potential TikTok Ban?!
As you may already know, there has been a lot of talk lately about the possibility of a TikTok ban. While this has not yet come to fruition, it's important to consider the implications this could have for businesses and recruiters who rely on TikTok as a platform to market their brand, recruit new talent, and connect with their audience.
The Effects of Workplace Racism and Sexism
One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
When Rage Applying Strikes: How to Identify Unserious Candidates
As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
How to Increase Job Ad Exposure
In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
How to Navigate Hiring Out of State
The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).