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Experience with streaming data ingestion, machine-learning, Apache Spark a plus. Hands-on experience developing a distributed data processing platform with Big Data technologies like Hadoop, Spark etc.
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Spark MLlib: Machine learning library built on Apache Spark for distributed data processing. Continuous Improvement : Stay updated with the latest advancements in artificial intelligence and machine learning research, tools, and techniques, identifying opportunities for innovation and improvement within the AI ecosystem.
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Our technology stack includes Java and Python as well as a wide range of internal tools built on top of Apache Spark, TensorFlow, and other Big Data technologies. As a Lead Engineer on the AI Ops team, you will be responsible for building the next-generation routing engine for the Internet using Data Science, Machine Learning (ML), and Artificial Intelligence (AI.
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Fluent in some of these machine learning frameworks such as SKLearn, XGBoost, PyTorch, or Tensorflow, and can leverage code as a strategic tool to shape innovative solutions. Proficient in Java and/or Python, their skills transform abstract machine learning concepts into robust, efficient, and scalable solutions.
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Experience with machine learning hardware, including AMD, NVIDIA DGX, or small form factor HW, such as Jetson or Xavier. Experience with distributable databases, including Apache Spark, HDFS, MapR, or Cloudera.
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Experience with big data batch processing tools: Hadoop MapReduce, Elasticsearch, PIG, Hive, Cascading/Scalding, Apache Spark, AWS Glue, AWS EMR. Desired Certifications: AWS Certified Cloud Practitioner, AWS Certified Database-Specialty, AWS Certified Data Analytics-Specialty, AWS Certified Machine Learning-Specialty, AWS Certified Solutions Architect Professional.
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Apache Kafka, Apache Flink, Apache Spark, Trino (Presto), Apache Airflow/Dagster, Apache Superset, AWS S3, Snowflake, Amplitude, CDP (e.g. Segment.com) The adjacent areas of major focus are Machine Learning Infrastructure and workflow, Experimentation Platform, Knowledge Graphs and various Data Science and Analytics related tooling.
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Experience with cloud-based machine learning platforms such as Amazon SageMaker or Apache Spark-based solutions like Databricks is advantageous. Cytokinetics is dedicated to advancing the frontiers of technology through the strategic application of artificial intelligence, machine learning, image analysis, and computational biology and chemistry.
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Hands-on experience with cloud platforms and technologies (e.g., AWS, Azure, Google Cloud Platform) and data engineering tools (e.g., Apache Spark, dbt, Flint, Kafka). Strong understanding of machine learning algorithms, techniques, and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Vertex AI.
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You have experience in building systems that orchestrate and execute complex workflows in big-data leveraging Apache Spark, Apache Kafka, and Hadoop stack preferably in Google Cloud Platform.
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Familiarity with Apache spark, databricks, Azure HDInsights or Synapse or Azure ML systems. We are looking for a Principal Software Engineer with a passion for solving hard problems, big data, ML Ops (Machine Learning operations), real time event processing, and building software at very large scale.
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Domain expertise: programming languages, data analytics, machine learning (ML/AI), DevSecOps, Cloud, Big Data. Demonstrate expert-level knowledge/experience in Big data and Cloud technologies: Spark ML, Splunk, Elastic Search, Apache NiFi, AWS Glue, Cribl.io Logstream, and Hadoop.
$110,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Implement advanced high-performance Python code for large-scale distributed computing environments such as Apache Spark, Hadoop/HIVE to develop scalable, reusable analytical and quantitative models.
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Big Data Offline Processing systems like Apache Spark, Pig, Hadoop or others. Technical leadership entails influencing search indexing, Search algorithms, recommendation algorithms, relevance & ranking, visual search, data mining, machine learning, data analysis & metrics, query processing, multi-lingual search, search UX, and overall Adobe Cloud ecosystem.
$118,500 - $219,100 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Specific tools may include (do not need experience with all): Python frameworks (e.g., Pandas, NumPy, Scikit-learn), SQL, Matplotlib, Seaborn, Plotly, Scikit-learn, TensorFlow, PyTorch, Apache Hadoop, Apache Spark, Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure, OpenRefine, Statistical Analysis.
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