AI Engineer (2021 Q4)

Austin TX or Toronto ON or Washington DC /
Software /
Full-time
About Cerebri AI
 
Cerebri AI is the creator of CVX, an end-to-end platform that automates AI processes from data engineering to the next best actions for multiple KPI and thus achieves CI. CVX 3 platform delivers the fastest time to market with production-ready BI and AI insights while not forgoing the quality that every enterprise or network operator expects from their analytics initiatives. Key to this performance is the fact that all processing on CVX is event-based.
 
CVX 3 platform implements Continuous Intelligence for classification, recommendation, and next best actions. It is designed to scale horizontally with data sources, event rates from said sources, KPIs management, BI insights, and AI insights. Continuous Intelligence ( CI ) is the ability to integrate raw data, calculate engineered data into datasets in real-time, score KPIs, generate insights seamlessly at scale. CI is essential to time-series processing. CI is the sine qua non for time-sensitive management of multiple Key Performance Indicators ( KPI ).
 
CI enables a slew of positive business outcomes and use cases:
·      Dynamic personalization: Serve content, propose products, promote services, or execute actions
·      Dynamic customer cohort creation: Determine cohorts of similar behavior or tuned to specific KPIs
·      Scalable actions across segments of customers
·      Usage-based/behavior-based pricing models: Insurance based on behavior
·      Abnormality and fraud detection: Identify and prevent unauthorized activity
·      Security and remediation: Detect issues and alert responders in exponentially less time than traditional security through intelligent analyses
·      Network performance: Monitor and respond to network performance issues faster
·      IoT analytics: Unify disparate data sources to reduce costs and improve performance
·      IOT TCO: Reduces the cost of installation by reducing tuning and maintenance 
 
How do we do this? We hire the best data scientists, mathematicians, and software developers and work as a cross-disciplinary team/gang/clan. We work hard, laugh hard, and impress our peers and clients. Because we can. And because we want to. To learn more, visit cerebriai.com. In the meantime, if you think you have what it takes, give us a spin and upload your resume.
 
"Cerebri AI was recognized as 2019 Cool Vendor for Customer Journey Analytics by Gartner."


Responsibilities

    • Architect, build, test, deploy distributed, scalable, and resilient Spark/Scala/Kafka Big Data processing, and Machine Learning model pipelines for batch, micro-batch, and streaming workloads sets into Cerebri AI’s proprietary data stores for use in machine learning modeling
    • Develop and maintain data ontologies for key market segments
    • Collaborate with data scientists to develop automated orchestration of model pipelines to solve Cerebri AI business use case objectives
    • Collaborate with clients to develop pipeline infrastructure, and to ask appropriate questions to gain a deep understanding of client data
    • Deploy fully containerized Docker/Kubernetes Data processing, and Machine Learning model pipelines into Azure, AWS, GCP cloud environments and on-premise systems as necessary
    • Document Detailed Designs (including source to target mappings) and Code for Data Quality frameworks that can measure and maintain Data Completeness, Data Integrity, and Data Validity between interfacing systems
    • Ensure all solutions comply with the highest levels of security, privacy, and data governance requirements as outlined by Cerebri and Client legal and information security guidelines, law enforcement, and privacy legislation, including data anonymization, encryption, and security in transit and at rest, etc.
    • Train and mentor junior team members
    • Acts as a Subject Matter Expert and a Thought Leader, continuously following industry trends, the latest competitive developments, and delivering papers and presentations at major industry conferences and events.

Qualifications

    • A degree in Computer Science, Engineering, AI, Machine Learning, BI, MIS, or an equivalent technology field
    • Minimum 2 years of Production programming experience in Scala, Spark, PySpark, Big Data, Python
    • Minimum 2 years of Production experience with the Hadoop Big Data platform
    • Able to program and understand data science and data engineering ideas in Python and translate into modular, functional components in Scala
    • Streaming and micro-batch application development experience would be an asset, including Kafka, Storm, NiFi, Spark Streaming, Confluent or equivalent
    • Proficiency with Linux/Unix operating systems, utilities, and tools
    • Experience working directly with relational database structures and flat files  
    • Ability to write efficient database queries, functions, and views to include complex joins and the identification and development of custom indices
    • Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, continuous integration and development, and operations.
    • Experience deploying containerized Docker/Kubernetes applications
    • Experience with Microsoft Azure or similar cloud computing solutions
    • Big Data application architecture experience and in-depth understanding of the Big Data ecosystem, applications, services, and design patterns
    • Production systems integration experience
    • Good verbal and written communication skills, with both technical and non-technical stakeholders

Nice to Haves

    • Experience in business intelligence visualization tools such as Grafana, Superset, Redash or Tableau.
    • Master’s degree or higher in a relevant quantitative subject
    • Experience with the Atlassian suite (JIRA, Confluence, BitBucket).
    • Any other related experience with Big Data, artificial intelligence, natural language processing, machine learning and/or deep learning, predictive analytics
    • Familiar with automated machine learning (AutoML) concepts would be an asset
    • Experience with Breeze would be an asset
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How do we do this? We hire the best data scientists, mathematicians, and software developers and work as a cross-disciplinary team/gang/clan. We work hard, laugh hard, and impress our peers and clients. Because we can. And because we want to. To learn more, visit cerebriai.com. In the meantime, if you think you have what it takes, give us a spin and upload your resume.


Specify your location preference if we were to move away from all remote.