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Company

Original Job Post

phData · 1 week ago

Senior Machine Learning Engineer

United States

Full-time

Remote

Senior Level

4+ years exp

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Hiring Manager

Lisa Leff

Insider Connection @phData

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Responsibilities

Design and create environments for data scientists to build models and manipulate data

Work within customer systems to extract data and place it within an analytical environment

Learn and understand customer technology environments and systems

Define the deployment approach and infrastructure for models and be responsible for ensuring that businesses can use the models we develop

Reveal the true value of data by working with data scientists to manipulate and transform data into appropriate formats in order to deploy actionable machine learning models

Partner with data scientists to ensure solution deployability—at scale, in harmony with existing business systems and pipelines, and such that the solution can be maintained throughout its life cycle

Create operational testing strategies, validate and test the model in QA, and implementation, testing, and deployment

Ensure the quality of the delivered product

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 LearningSoftware EngineeringData EngineeringPythonScalaJavaData PipelinesSQLDistributed SQL QueriesData Science LibrariesDockerKubernetesContainerizationData Source SystemsNetwork ArchitectureCloud ArchitectureLinuxStorage SystemsAWSSparkPandasAPIsFlaskDjangoSpringSoftware Development LifecycleProblem-SolvingCommunicationAnalytical AbilitiesEcosystem Technologies

Required

At least 4 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer

4-year Bachelor's degree in Computer Engineering or a related field

Experience deploying data science models in a production setting.

Expertise in Python, Scala, Java, or another modern programming language

The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets

Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries

Experience working with Data Science/Machine Learning software and libraries such as h2o, TensorFlow, Keras, scikit-learn, etc.

Experience with Docker, Kubernetes, or some other containerization technology

Familiarity with multiple data source systems (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP)

Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), storage systems (e.g., AWS, Databricks, Cloudera)

Production experience in core data technologies (e.g. Spark, Pandas)

Development of APIs and web server applications (e.g. Flask, Django, Spring)

Complete software development lifecycle experience including design, documentation, analytical abilities; ability to translate business requirements and use cases into a solution, including ingestion of many data sources, ETL processing, data access, and consumption, as well as custom analytics

Excellent communication and presentation skills; previous experience working with internal or external customers

Preferred

A Master’s or other advanced degree in data science or a related field

Hands-on experience with one or more ecosystem technologies (e.g., HBase, Impala, Solr, Kudu, Streamsets, NiFi, ElasticSearch, Databricks, Snowflake, AWS/Azure/GCP)

Relevant side projects (e.g. contributions to an open source technology stack)

AWS Sagemaker, MLFlow experience

Benefits

Remote-First Work Environment

Competitive comp

Excellent benefits

4 weeks of PTO plus 10 Holidays

Company

phData

phData Premier provider of Big Data managed services and architecture, engineering, and data science consulting.

Founded in 2014

Minneapolis, Minnesota, USA

501-1,000 employees

https://www.phdata.io/

H1B Sponsorship

phData has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Trends of Total Sponsorships

2023 (3)

2022 (14)

2021 (14)

2020 (8)