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NoSQL databases, and data processing frameworks (e.g., Apache Spark). Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
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Primary focus on Java application development and enhancements using Java, Python, SQL, Snowflake DB, Databricks spark/Notebook, Azure Blob storage. Familiarity with Databricks and/or Snowflake is a plus.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency.
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Strong understanding of data engineering concepts and experience with tools such as SQL, NoSQL databases, and data processing frameworks (, Apache Spark). Experience with cloud platforms (, AWS, Azure, GCP) and containerization technologies (, Docker, Kubernetes) is a plus.
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VantAI is building a computational pipeline combining state-of-the-art physics-based modeling and machine learning to revolutionize drug discovery and development. You will work with a team of world-class machine learning engineers in an interdisciplinary, research-heavy position on a range of unsolved problems around representation learning of proteins, small molecules, biological networks and genomics.
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The ideal candidate will have a strong background in AWS, Redshift, Snowflake, dbt, Python, building ETL pipelines, and Machine Learning. Collaborate with data scientists and analysts to support machine learning initiatives and advanced analytics.
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This role focuses on developing, deploying, and managing scalable machine learning solutions within our tech stack that includes Snowflake, dbt, Python, Kubernetes, and Java. The ideal candidate will have a strong foundation in software engineering and data infrastructure, as well as a proven ability to implement efficient, scalable, and robust decisioning platforms.
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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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Formulate and refine existing strategies specific to RAG and chatbot capabilities, ensuring that they are aligned with the Service OKRs (Objectives and Key Results) and any complementary efforts in other digital channels, and that they leverage appropriate technologies and best practices in natural language processing, machine learning, and knowledge retrieval.
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Experience with Snowflake, Databricks/EMR/Spark, and/or Airflow. Familiarity with Agile Scrum principles and ceremoniesPreferred Qualifications 2+ years of work experience implementing and reporting on business key performance indicators in data warehousing environments, exposure to reliability engineering best practices a plus.
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Experience and understanding of various core AWS services such as IAM, Cloud Formation, EC2, S3, EMR/Spark, Glue, Datasync, CloudHealth, CloudWatch, Lambda, Athena, and Redshift. Solid experience of AWS services such as CloudFormation, S3, Glue, EMR/ Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, SM etc.
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Expert level knowledge of Cloudera Hadoop components such as HDFS, Sentry, HBase, Kafka, Impala, SOLR, Hue, Spark, Hive, YARN, ZooKeeper and Postgres. Hadoop Admin Ops / SRE role supporting Platforms built around Big Data Technologies (Hadoop, Spark, Kafka, Impala, Hbase, Docker-Container, Ansible and many more.
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Senior Machine Learning Engineer (Python, Spark, MLOPS, Cloud) New York City (Hybrid On-Site): $165,100 - $188,500 for Senior 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.
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Successful candidates will demonstrate scientific excellence and outstanding achievements applying advanced machine learning, artificial intelligence and computational sciences in human health.
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machine learning apache spark plus jobs Company: Eightfold in New York, NY
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