Ideally you have an in-depth understanding of streaming data technologies like Amazon Kinesis or Apache Kafka, and experience with open-source data processing frameworks like Apache Spark, Apache Flink, or Apache Storm.

More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.

Python or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.

Technical Proficiency: Expertise in SQL and programming languages such as Python; familiarity with big data technologies like Apache Hadoop, Spark, and Kafka. Mentorship: Mentor and coach peers on data standards and best practices, promoting a culture of continuous learning and improvement.

Production-level experience with core quantitative analysis techniques (e.g., predictive modeling, machine learning, artificial intelligence, or natural language processing) in a consulting environment.

Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. Experience in operating a workload/workflow management system (e.g. Slurm, Apache Airflow/Beam/Flink.

Foundation Model Infrastructure team, within Machine Learning Platform Technologies organization is the back-bone of Apple Intelligence. Familiar with fundamental Deep Learning architectures such as Transformers, Encoder/Decoder models.

Design and implement sophisticated machine learning models for object detection, classification, semantic segmentation, and anomaly detection specific to autonomous driving scenarios. The ideal candidate is an expert in applying artificial intelligence and machine learning to the challenges of autonomous navigation.

F5, Inc. seeks Data Scientist II in Seattle, WA:Job Duties: Build machine learning algorithms and statistical models to detect traffic anomalies, L7 DDoS attacks and Web Application Firewall false positive detections.

We are doing the world-class work in machine learning, computer vision, natural language processing, speech and audio, knowledge and data mining, and transferring our work into ByteDance which are used by hundreds of millions of users around the world.

Develop and implement scalable and reproducible machine learning pipelines for 3D shape quantification on data from microscopy image-based assays. We seek a motivated, knowledgeable, and team-oriented scientist with excellent machine learning knowledge, interested in applying these skills to biology as part of the Computational Cell Science team in the Allen Institute for Cell Science.

Expertise in streaming technologies (Apache Spark, Hadoop, Kafka) At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs.

Experience with neural deep learning methods and machine learning. Machine learning (ML) has been strategic to Amazon from the early years. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.