- UpvoteDownvoteShare Job
- Suggest Revision
Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$248,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow. 8+ years of progressive experience as a data analytics, machine learning engineer or similar roles. Architect, develop and manage machine learning model development and deployment lifecycle to launch GenAI and ML services end to end.
$210,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with cloud computing environments, including Databricks using Spark. As a data scientist, you’re excited at the prospect of unlocking the secrets held by a data set, and you’re fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence.
$172,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Experience with Python, Apache Spark (PySpark, Databricks), DevOps Tools (Git, Github Actions, Docker, etc.) Hands-on experience in implementing and training machine learning algorithms and statistical analyses, including for example non-parametric tests, linear mixed models, modern supervised and unsupervised machine learning algorithms such as SVM, random forest, PCA, t-SNE, clustering, deep learning, and LLMs.
$190,400 a yearFull-timeRemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning EngineerSan Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning EngineerRemote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning Engineer.
Full-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Spark, Presto/AWS Athena) Eseguire l'analisi statistica e la modellazione utilizzando tecniche di machine learning e signal processing. Conoscenza di analisi statistiche, algoritmi e tecniche di machine learning.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Hands-on experience working with Hadoop, Hive, Pig, Map Reduce, Spark, Rabbit MQ, Kafka, Flume. This engineer will assume wide-ranging projects regarding ETL, migration of processes and services from on-premises to cloud environments, Artificial Intelligence/Machine Learning (AI/ML), machine translation, and similar efforts.
Full-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Machine Learning Engineer. 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.
$201,400 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Experience with natural language processing, text mining, or machine learning techniques. Experience with distributed data and computing tools, including MapReduce, Hadoop, Hive, Kafka, Spark, or MySQL.
$220,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
- Suggest Revision
The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark) for scalable data processing and model deployment. Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and proficiency in programming languages such as Python or R.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively. Experience with applied machine learning (tree-based methods, ensemble methods, neural networks/deep learning.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Machine learning background with algorithms Expertise in MLOps and DataOps lifecycles and engineering implementation in enterprise Fluency with Python (AI/Client specific packages, libraries), Spark or R (optional) Soft skills: Strong ability in communicating in writing or verbally, copywriting, planning and distributing communication, etc.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Strong grasp of distributed data processing tools such as Apache Spark, Kafka, as well as AWS Cloud Native Services. Your expertise in data science, statistical modeling, and machine learning will be critical in developing and executing strategies that optimize data collection and streamline recommendations for our customer.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Familiarity with Machine Learning / Artificial Intelligence concepts is highly desired. Bachelors Degree with 12 years of relevant experience (or Masters Degree with 10 years experience) with enterprise level SDLC. , About Metronome, LLC Metronome is a spark that ignites passion for our customers and each other.
Full-timeExpandApply NowActive JobUpdated Today
learning spark jobs in Mclean, VA
FEATURED BLOG POSTS
Tips for a Good Character Reference Letter with Examples
Hiring managers love a resume laden with relevant skills and qualifications. Hard skills specific to the role, like SEO strategy or Java programming languages, are easy to qualify using achievements or facts and figures. But how exactly can they verify personality traits, work ethic, relationship management skills, or curious nature during an interview when they barely know you?
How to Dress on the First Day of Work (Men & Women)
You did it! Out of hundreds of applicants and dozens of people interviewed, you’re the one who got a new job. Congrats! Now comes the question of how to dress on the first day of work.
Why College Students Should Work While in College?
College is a special part of our lives. It’s a time when we prepare for our dream job while creating some of the most memorable moments in life. That said, college life can also be stressful. Not only do we have to spend long hours studying, writing and researching, but we also have to deal with increased tuition fees and living expenses.
5 Ways to Measure Candidate Experience
Your candidate experience is made up of 4 essential parts
How to Stall a Job Offer Politely
You did it! After several weeks of looking for a new job and undergoing grueling interviews, you finally have a job offer. Although this may be very exciting, accepting a job offer means that you’re making a long-term commitment to your future employer. So, even if you’re eager to leave your current job, this isn’t a decision you should take lightly.
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.