Machine Learning Engineer
Cerebri AI
 Washington, DC
About Cerebri AI
Cerebri AI is an advanced customer analytics company that uses state-of-the-art AI technologies, such as SHARP reinforcement learning, to analyze customer touchpoints across multiple channels. Cerebri's AI solutions quantify a customer’s commitment to a brand or a product, at any point in time, expressed in monetary values and derive Best Actions that drive customer commitment and financial results.

After nearly two years in semi-stealth mode devoted to developing a truly world-class product, our Series A financing was led by M12 (formerly Microsoft Ventures). To date, the team has filed 11 patents pertaining to the Cerebri AI way. We now have 60 employees in three offices in Austin, Toronto and Washington DC. Over 80% of the staff are in technical roles in data science and software engineering. Our team of senior executives averages 20+ years selling software successfully to enterprises worldwide. Cerebri AI is a proud Microsoft Partner and an active member of the Mastercard Start Path network.
To learn more, visit cerebriai.com.

“Cerebri AI was named a 2019 Cool Vendor in Artificial Intelligence for Customer Analytics by Gartner“

Role:As a Machine Learning Engineer, you will play an integral role in the development of our flagship AI product offerings for enterprise. You will be part of a small, focused team working in fast paced environment.

Responsibilities

  • Architect, build, test, deploy distributed, scalable, and resilient Spark/Scala/Kafka Data processing, and Machine Learning model pipelines for batch, micro-batch, and streaming workloads
  • Collaborate with data engineers to develop automated orchestration of data pipelines to find signals in client data
  • Collaborate with data scientists to develop automated orchestration of model pipelines to solve Cerebri AI business use case objectives
  • Proven experience in test automation for data and model pipelines
  • 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
  • 3+ years of production programming experience in Scala (emphasis in functional programming), Spark and Python
  • Proven experience in Spark (strong knowledge optimizing code for Spark jobs)
  • Able to program and understand data science and data engineering ideas in Python and translate into modular, functional components in Scala
  • Familiar with automated machine learning (AutoML) concepts would be an asset
  • Experience with Breeze would be an asset
  • Experience deploying containerized Docker/Kubernetes applications
  • Streaming and micro-batch application development experience would be an asset, including Kafka, Storm, NiFi, Spark Streaming, Confluent or equivalent
  • Production systems integration experience
  • Proficiency with Linux/Unix operating systems, utilities and tools
  • Big Data application architecture experience and in-depth understanding of the Big Data ecosystem, applications, services, and design patterns

Nice To Haves

  • 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

  • Problem Solver – You are proficient at using a combination of intuition and logic to come up with solutions
  • Detail Oriented – You are an expert at identifying nuances and aligning small details with larger objectives
  • Independent Worker – Your experience and capabilities allow you to require little instruction and guidance
  • Excellent team player – You are humble, ambitious and driven to make a difference