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Knowledge of distributed computing technologies such as Apache Spark, Hadoop, or Dask, and experience with containerization and orchestration technologies such as Docker and Kubernetes. Position Overview: As a Machine Learning Infrastructure Engineer, you'll play a crucial role in designing, building, and optimizing our machine learning infrastructure to support the needs of our organization.
$150,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience debugging and optimizing large scale data pipelines using Apache Spark. The Machine Learning Infrastructure organization provides infrastructure and support to run machine learning workflows and ship to production, tooling and operational capacity to accelerate the use of these workflows, and opinionated technical guidance to guide our users onto successful paths.
$254,600 - $382,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Strong understanding and experience with distributed systems like Apache Spark, Ray etc. Voxel is building the future of Computer Vision and Machine Learning for operations, risk, and safety.
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Excellent debugging, analytical and problem-solving skillsA deep understanding of machine learning foundations and can develop technical solutions for new problemsNice to have:Experience working with cloud data processing technologies (Apache Spark, ElasticSearch, Presto, SQL, etc.
$65,000 - $400,000 a yearFull-timeExpandApply NowActive JobUpdated 4 months ago - UpvoteDownvoteShare Job
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Experience with big data technologies such as Apache Spark or Hadoop Preferred. Experience in Machine Learning engineer or Infrastructure roles, with a focus on Machine Learning infrastructure.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn). Job Title: ML Infrastructure Engineer with GCP. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn.
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Strong programming skills in languages such as Python, Java, or Scala, with experience in distributed computing frameworks like Apache Spark or TensorFlow. Position Overview: As the Lead Machine Learning Infrastructure Engineer, you'll play a pivotal role in leading our machine learning infrastructure initiatives and driving the design, development, and optimization of our infrastructure solutions.
$200,000 - $300,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Experience working with cloud data processing technologies such as Apache Spark, ElasticSearch, Presto, SQL, etc. You will be building products using technologies such as AWS SageMaker, Tensforflow, Pytorch, LLM, Elastic Search, REST web services, SQS/Kafka, Vector Database, HBase, Machine Learning, and more.
Full-timeExpandApply NowActive JobUpdated 19 days ago - UpvoteDownvoteShare Job
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Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform). Strong understanding of Containerization technologies (e.g., Docker, Kubernetes). Experience with cloud platforms such as AWS, GCP, or Azure.
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Job Title: ML Infrastructure Engineer with Google Cloud Platform. Job Title: ML Infrastructure Engineer with Google Cloud Platform. Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure.
Full-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Experience with Spark, MLLib, Databricks,MLFlow, Apache Airflow, Dagster and similar related technologies. Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure.
Full-timeExpandApply NowActive JobUpdated 20 days ago - UpvoteDownvoteShare Job
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GCP experience is strongly preferred. Proficiency in programming languages Python, Java. Excellent problem-solving and communication skills.
ExpandApply NowActive JobUpdated 20 days ago - UpvoteDownvoteShare Job
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Familiar with Spark, MLLib, Databricks,MLFlow, Apache Airflow, Dagster and similar related technologies. Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow.
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Developing data pipelines powered by Apache Spark and other modern big data processing systems. Building infrastructure that enables deploying machine learning models over billions of historical data points collected from tens of thousands of retail stores across the US.
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