Lead ML/AI Engineer
Position Summary:
- As a Lead ML/AI Engineer, you will drive the design and implementation of functionality related to the end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform, leveraging and integrating the cloud native services with other standard operational and automation tools. Key responsibilities include:
- 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 model and data.
- Ability to 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.
- Innovative thinking and great communication skills.
- Strong ownership of deliverables, with design decisions aligned to scale and industry best practices.
- 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.
- Design, implement, and optimize machine learning algorithms and models. Stay abreast of the latest advancements in ML research and apply them to solve complex business problems.
- Architect and implement scalable and efficient machine learning systems. Collaborate with software engineers to integrate ML models into production systems.
- Work closely with data engineers to ensure the availability and quality of data for training and evaluation of machine learning models.
- Develop strategies for deploying machine learning models at scale. Ensure models are integrated into production systems with high reliability and performance.
- Design and conduct experiments to evaluate the performance of machine learning models. Iterate on models based on feedback and evolving business requirements.
Required Qualifications:
- 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: bachelors degree in computer science, Engineering, Statistics, Physics, Math, or related field or equivalent experience
- Preferred: masters degree or PhD with coursework focused on advanced algorithms, mathematics in computing, data structures, etc.
Preferred locations:
Dallas/Irving, Chicago, Boston/Wellesley, NYC, Hartford CT, Blue Bell PA, Scottsdale AZ, or Woonsocket RI.
Originally posted on