- UpvoteDownvoteShare Job
- Suggest Revision
In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Engineer ( Data Extraction ), you can expect to earn up to $210,000 (depending on experience), highly competitive benefits and equity. Machine Learning Engineer (Data Extraction.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Expertise with CI/CD processes and contributes to a sustainable and robust codebaseExperience with batch jobs/data pipelines and is comfortable deploying through these systems (i.e. Airflow, Luigi, Composer)Build and interact with production systems for serving machine learning predictions.
$185,000 - $220,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
- Suggest Revision
We are looking for a passionate Software Engineer, Big-Data Engineer, Machine-Learning Engineer, Full-stack Engineer, or UI/UX Engineer, who can contribute and make a difference in any of the different components of our Knowledge Graph Platform.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Demonstrated expertise through publications in top tier venues in fields such as machine learning, NLP, artificial intelligence, computer vision, optimization, computer science, statistics, applied mathematics, or data science.
InternExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
$101,000 - $200,050 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
As a Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of Excellence within the Machine Learning Center of Excellence, you will have the unique opportunity to apply sophisticated machine learning methods to a wide variety of complex tasks.
Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Deep knowledge in Machine Learning, Deep Learning, Data Mining, Information Retrieval, Statistics. Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
From Amazon.com to world class machine learning pipelines, from cutting-edge digital healthcare to no-checkout retail, we push the boundaries of technology in every direction using the globe’s largest AWS deployment.
$143,300 - $247,600 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Certification in cloud platforms (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer). We are looking for a proficient Software/Data Engineer specializing in Directed Acyclic Graphs (DAGs) and dependency graph orchestration.
Full-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Engineer ETL frameworks with cutting-edge technologies such as Snowflake, Airflow, Apache Spark, Python etc. Onboard data by working with different sources/stores of data (OneTick, CQG, ICE, Bloomberg, Refinitiv, etc.
$150,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Plus - Experience with Machine Learning and Artificial Intelligence. As Senior Data Engineer, you will. Familiarity with data pipeline and workflow management tools (e.g., Airflow, DBT Kafka.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Promote modern approaches in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLMs) within the computational and data ecosystem to advance researcher productivity and scientific discovery.
$183,854 - $289,990 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
The ideal candidate will have experience with Python, Data Engineering, AWS, and databricks. Optimize data storage, retrieval, and processing using services like Amazon S3, Redshift, Glue, and Athena.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Define and implement the "intents" and "entities" that define the conversation interaction, along with building human language data sets to train machine learning models driving the virtual assistant.
$84,000 - $179,200 a yearFull-timeExpandApply NowActive JobUpdated Today
data engineer machine learning jobs Company: Deloitte in New York, NY
FEATURED BLOG POSTS
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).
Building a Candidate Pipeline Through Internships
Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
Hiring Transparency
Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
Recruitment strategies that are weird, but actually work
In the current candidate-driven job market, recruiters are looking for unique ways to attract talent. Some have resorted to even (dare we say it?) recruitment strategies on the border of weird and wacky. What can we learn from the unusual recruitment tactics that are being used and actually getting results? Here’s a rundown of some unique recruitment strategies that actually work.