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Hands-on experience using Databricks or Apache Spark (i.e., PySpark, SparkR, or Scala) and understanding best practices. Masters degree and 3 years of Machine Learning Engineer, Data Engineer, Software Engineer, or Data Scientist OR.
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Experience with Hadoop/Hive, Neo4J, Apache Spark, Kafka and MongoDB is a plus. BCforward is currently seeking a highly motivated Data Science/Machine Learning developer for an opportunity in Jersey City, NJ.
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We are currently seeking a Data Technical Lead (Apache Spark, Pyspark and Databricks) to join our team in Dallas , Texas (US-TX) , United States (US). In-depth knowledge of Apache Spark, Pyspark and Databricks architecture.
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Advance Analytics: Python, R Studio, Data R obot , DataBricks MLflow , AWS Sagemaker, Azure Machine Learning Studio. Big Data: Azure Stream Analytics, Azure HDInsight, Amazon E lastic Map Reduce (EMR) , AWS Athena, Apache Spark, Hadoop, Hive.
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Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML. Experience with Big Data platforms such as Databricks or Apache Spark.
$82,000 - $236,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Model Integration & Scalability: Collaborate with cross-functional teams to integrate data science solutions into scalable, production-grade systems using open-source frameworks like Apache Spark and containerization technologies like Docker.
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Direct Client Sr Lead Data Engineer Apache Spark, Spark Core, Spark SQL Data Bricks. Direct Client - Sr Lead Data Engineer Apache Spark, Spark Core, Spark SQL, Spark StreamingData Bricks.
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Sr. No Skill Technical Area Must Have/Good to have Proficiency Rating (1 to 5) 1 Data Bricks •Strong hands on in Pyspark and Apache Spark. Experience in Native Spark Migration to Databricks.
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Big Data Technologies:Distributed Computing: Tools like Apache Spark, Hadoop. Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Data science, machine learning, optimization models, PhD 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.
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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.
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Keywords: Golang, Web Application, Backend, Gin, Go kit, Java, Spring Boot, MySQL, PostgreSQL, MongoDB, Cassandra, CI/CD, Docker, Kubernetes, Communication, Collaboration, Teamwork, Learning, Growth, Agile (optional), Big Data (optional), Apache Spark (optional), Hadoop (optional), Google Cloud Platform (optional), Cloud Functions (optional), Cloud Run (optional), Cloud SQL (optional), Cloud-Native (optional.
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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.
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Knowledge of cloud & computing technologies such as: Hadoop, Apache Spark, AWS, Microsoft Azure or Google cloud. Experience with machine learning tools such as scikit-learn, R, Theano, TensorFlow, SparkML, or Foundry.
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We use various open-source technologies (such as Apache Spark, Presto, Comet, Apache Airflow to name a few) to develop services for Adobe customers and partners. Plus, to be a Committer or PMC Member with the Apache Software Foundation on big data technologies: Apache Spark, Hadoop Stack, Kafka, Comet, Atlas, delta.
$154,000 - $278,800 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago
machine learning apache spark jobs Company: Diverse Lynx
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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?
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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.
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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.
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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.