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Lead AI/ML Engineer

2 months ago

Irving, Texas, United States Acunor Inc Full time
Job Title: Lead AI/ML Engineer

At Acunor Inc, we are seeking a highly skilled Lead AI/ML Engineer to join our team. As a key member of our data science team, you will be responsible for driving the design and implementation of functionality related to the end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform.

Key Responsibilities:

  • Support the deployment of ML/AI pipelines on the platform.
  • Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment, and monitoring of models and data.
  • Translate functionality into scalable, tested, and configurable platform architecture and software.
  • Establish strong software engineering principles for development in Python on the Azure/Google Cloud Platform.
  • Deliver features aligned to enterprise AutoML, Feature Engineering, and MLOPS capability.
  • Provide technical leadership and mentorship to a team of machine learning engineers.
  • Collaborate with cross-functional teams to align ML initiatives with overall business goals.

Requirements:

  • 6+ years of experience in analytics domains, and deep understanding of ML operationalization and lifecycle management.
  • 5+ years of deploying and monitoring analytical assets in batch/real-time business processes.
  • 5+ years of SQL & Python programming experience leveraging strong software development principles.
  • Experience in designing and developing AI applications and systems.
  • Experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Pub/Sub, Kafka, Spark Streaming etc.)
  • Experience with REST API/Microservice development using Python/Java.
  • Experience with deployment/scaling of apps on containerized environment (AKS and/or GKE)
  • Experience with Snowflake/Big Query, Google Dataproc/Databricks or any big data frameworks on Spark
  • Experience with RDBMS and NoSQL Databases and hands-on query tuning/optimization.

Preferred Qualifications:

  • Hands on experience in building solutions using cloud native services (Azure, GCP preferred)
  • Understanding of DevOps, Infrastructure as Code, automation for self service

Education:

  • Required: bachelor's degree in computer science, Engineering, Statistics, Physics, Math, or related field or equivalent experience
  • Preferred: master's degree or PhD with coursework focused on advanced algorithms, mathematics in computing, data structures, etc.