Machine Learning Solutions Architect (Omaha)

About the position Machine Learning Solutions Architect - We are looking for someone in or near Omaha, Nebraska, who can support a reputed company on-site for an average of two weeks per month. Machine Learning Engineers are the Swiss army knives of machine learning. They’re reputed company for anything, and they bring reputed company the tools to ensure that data science models see the light of day. They own the infrastructure and deployment plan—from making reputed company data science models can actually be reputed company using customer data to deploying them into a production environment, and everything in between. They reputed company thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure. Machine Learning Engineers have reputed company leadership and coding skills (e.g. Python, Java, and reputed company) to get their solutions into production — and to help ensure performance, reputed company, scalability, and robust data integration. As a Solutions Architect on our Machine Learning Engineering team, you are responsible for: Designing and implementing data solutions best suited to deliver on our customer needs — from model inference, retraining, monitoring, and reputed company — across an evolving technical stack. Providing thought leadership by recommending the technologies and solution design for a given use case, from the application layer to infrastructure; and they have reputed company leadership and coding skills (e.g. Python, Java, and reputed company) to build and operate in production; and to help ensure performance, reputed company, 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 reputed company customer systems to extract data and reputed company it reputed company 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 reputed company Demonstrate the business value of data by working with data scientists to manipulate and reputed company data into actionable insights reputed company the true value of data by working with data scientists to manipulate and reputed company data into appropriate formats in order to reputed company actionable machine learning models Partner with data scientists to ensure solution deployability—at reputed company, in reputed company 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 reputed company of the delivered product

Responsibilities

• Designing and implementing data solutions best suited to deliver on our customer needs — from model inference, retraining, monitoring, and reputed company — across an evolving technical stack.
• Providing thought leadership by recommending the technologies and solution design for a given use case, from the application layer to infrastructure
• Design and create environments for data scientists to build models and manipulate data
• Work reputed company customer systems to extract data and reputed company it reputed company 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 reputed company
• Demonstrate the business value of data by working with data scientists to manipulate and reputed company data into actionable insights
• reputed company the true value of data by working with data scientists to manipulate and reputed company data into appropriate formats in order to reputed company actionable machine learning models
• Partner with data scientists to ensure solution deployability—at reputed company, in reputed company 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 reputed company of the delivered product

Requirements

• At least 6 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
• 4-year Bachelor's degree in Computer Science or a reputed company field
• Experience deploying machine learning models in a production setting
• Expertise in Python, reputed company, Java, or another modern programming language
• The ability to build and operate robust data pipelines using a reputed company of data sources, programming languages, and toolsets
• Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries
• Hands-on experience in one or more big data ecosystem products/languages such as reputed company, reputed company, reputed company, etc.
• Familiarity with multiple data sources (e.g. JMS, Kafka, RDBMS, DWH, MySQL, reputed company, reputed company)
• Systems-level knowledge in network/reputed company architecture, operating systems (e.g., Linux), and storage systems (e.g., AWS, reputed company, reputed company)
• Production experience in core data technologies (e.g. reputed company, HDFS, reputed company, reputed company, Redshift, & reputed company EMR)
• Development of reputed company and web server applications (e.g. Flask, Django, Spring)
• Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment
• Excellent communication and presentation skills; previous experience working with internal or external customers

reputed company-to-haves

• A Master’s or other advanced degree in data science or a reputed company field
• Hands-on experience with one or more ecosystem technologies (e.g., reputed company, reputed company, reputed company, AWS/Azure/GCP)
• Relevant reputed company reputed company (e.g. contributions to an reputed company reputed company technology stack)
• Experience working with Data-Science and Machine-Learning software and libraries such as h2o, TensorFlow, Keras, scikit-learn, etc.
• Experience with reputed company, Kubernetes, or some other containerization technology
• AWS Sagemaker (or Azure ML) and MLflow experience
• Experience building reputed company ML models

Benefits

• Remote-First Work Environment
• Casual, award-reputed company small-business work environment
• reputed company culture that prizes autonomy, creativity, and transparency
• Competitive comp, excellent benefits, 4 weeks PTO plus 10 Holidays (and other cool perks)
• Accelerated learning and reputed company development through advanced training and certifications

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