Job Description
Unlock future opportunities at phData where innovation meets data excellence. At phData we’re always on the lookout for top talent and we’re committed to expanding our network of skilled professionals. As our requirements evolve we encourage you to apply and submit your resume here even if there’s no role available at the moment. Your information will be added to our system and we’ll notify you of relevant opportunities as they become available if you are a fit.
Machine Learning Engineers are the Swiss army knives of machine learning. They’re ready for anything and they bring all the tools to ensure that data science models see the light of day. They own the infrastructure and deployment plan—from making sure data science models can actually be built using customer data to deploying them into a production environment and everything in between. They provide thought leadership by recommending the right technologies and solutions for a given use case from the application layer to infrastructure. Machine Learning Engineers have the team leadership and coding skills (e.g. Python Java and Scala) to get their solutions into production — and to help ensure performance security scalability and robust data integration.
What you’ll do in this role:
-
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
Required Experience:
-
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 ong 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 Experience
-
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
Why phData? We offer:
-
Remote-First Work Environment
-
Casual award-winning small-business work environment
-
Collaborative culture that prizes autonomy creativity and transparency
-
Competitive comp excellent benefits 4 weeks PTO plus 10 Holidays (and other cool perks)
-
Accelerated learning and professional development through advanced training and certifications
#LI-DNI
Date Posted
09/23/2024
Views
1
Similar Jobs
Engineering Manager - Software Supply Chain Security: Auth Infrastructure - GitLab
Views in the last 30 days - 0
This job description highlights a leadership role in developing secure scalable authentication infrastructure for GitLab It emphasizes technical exper...
View DetailsStaff Salesforce Engineer - CRM Systems - GitLab
Views in the last 30 days - 0
This job description outlines a Staff Salesforce Developer role focusing on designing building and scaling enterprisegrade solutions across Salesforce...
View DetailsGrowth Product Lead - Loyalty - Trafilea
Views in the last 30 days - 0
Trafilea promotes itself as a transformative consumer tech platform with AIdriven growth solutions highlighting achievements like 1B revenue and globa...
View DetailsSales Prospecting Account Executive - Financial Solutions - Blackbaud
Views in the last 30 days - 0
This job posting seeks Prospect Account Executives to sell Financial Management applications for nonprofits and governments Responsibilities include s...
View DetailsSolutions Architect - phData
Views in the last 30 days - 0
This job posting seeks a Solutions Architect to join phDatas Elastic Platform Operations team focusing on cloudnative data platforms like Snowflake AW...
View DetailsTeam Lead - Publisher Success Management (AdTech) - MGID
Views in the last 30 days - 0
MGID is a fastgrowing digital advertising company seeking a resultsdriven Team Lead to oversee client relationships and drive business growth in the U...
View Details