200+ applicants

Company

AllCloud · 1 day ago

Machine Learning Engineer

United States

Full-time

Remote

Mid Level

3+ years exp

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Cloud ComputingCloud Data Services

Actively Hiring

Hiring Manager

Frank Pullella

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Responsibilities

Keep our customers’ data separated and secure to meet compliance and regulations requirements.

Design, Build and Operate the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and cloud (mainly AWS) migration and ‘big data’ technologies.

Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operation problems.

Design, Build and Operate large, complex data lakes that meet functional / non-functional business requirements.

Optimize various data types ingestion, storage, processing, and retrieval from near real-time events and IoT to unstructured data as images, audio, video and documents, and in between.

Use Jupyter Notebooks to build and deploy ML models.

Leverage AWS AI/ML pre built solutions to accelerate work for customers.

Work with customers and internal stakeholders, including the Executive, Product, Data, Software Development, and Design teams, to assist with data-related technical issues and support their data infrastructure and business needs.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Machine LearningAWSSQLPythonBig Data ToolsData EngineeringDeep LearningNoSQL DatabasesJavaScalaElasticSearchHadoopKafkaKinesisMySQLPostgresDynamoDBCassandraAWS EC2AWS RDSAWS EMRAWS RedshiftNLPData TransformationMetadata ManagementWorkload ManagementMessage QueuingStream Processing

Required

3+ years of experience in a Data Scientist/Machine Learning Engineer role

Bachelor's (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems, or another quantitative field

Experience with big data tools: Spark, ElasticSearch, Hadoop, Kafka, Kinesis etc.

Experience with relational SQL and NoSQL databases, such as MySQL or Postgres and DynamoDB or Cassandra

Experience with AWS cloud services: EC2, RDS, EMR, Redshift etc.

Experience with functional and scripting languages: Python, Java, Scala, etc.

Experience with various ML models for classification, scoring and more

Experience with Deep Learning Neural Networks (Convolution, NLP etc.)

Experience with AWS AI/ML Services

Experience with Python coding

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases

Experience building and optimizing ‘big data’ data pipelines, architectures and data sets

Strong analytic skills related to working with unstructured datasets

Build processes supporting data transformation, data structures, metadata, dependency and workload management

Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores

Experience supporting and working with external customers in a dynamic environment