AI/ML Engineer

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Machine Learning (ML)
Artificial intelligence
Amazon Web Services
Machine Learning Operations (ML Ops)
AI/ML
AWS
Python
SQL
PySpark
Docker
DevOps
Agile
Lambda
sagemaker
cloud formation
Kinesis
Code commit
Code pipeline

Job Details

Hi,

Greetings from AB Technologies!

Job Title: AI/ML Engineer

Location: Chicago, IL (Hybrid)

Contract: 12+ Months W2 only

Required Skills and Experience:

  • Maintain and enhance existing ML models to maximize the performance and impact of the models
  • Leverage AWS services with appropriate consideration for scale and latency
  • Participate in Agile ceremonies as needed
  • Liaison between AI/ML team, data engineering and others as needed

Expertise in

  • AWS cloud services
  • Expertise in Python, SQL, PySpark, Docker
  • Experience with streaming and batch data architectures at scale
  • Experience operating in an Agile Methodology environment.
  • Experience with DevOps and CI/CD concepts

Some additional details on day to day needs.

Responsibilities:

  • Managing ML/AI Maturity levels, and helping set the direction on how to improve ML processes and Architectures.
  • Optimize & Automate model development and deployment processes.
  • Work alongside the team in any other capacity from optimizing model deployments to supporting training and registering models with metrics to the model registry.
  • Be an SME in MLOps and strong familiarity with the MLOps landscape.
  • Enhance the Model Development and Deployment lifecycle across the Analytics Organization.

Tools:

  • AWS proficiency (Lambda, SageMaker, Cloudformation, Kinesis, Codecommit, CodePipeline, Codebuild, CodeArtifact, State Machines, Airflow)
  • Experience with CI/CD (CodeBuild, CodePipeline)
  • Cloudformation/IaaC experience
  • Experience with Distributed computing (i.e. Spark)
  • Knowledge of different Machine Learning and Deep Learning Techniques and how to optimize models for latency.
  • Strong understanding of the MLOps life cycle (explainability, observability, feature store, model deployment automation, model testing, feature engineering)

Thanks & Regards,

Jayanth

AB Technologies Inc.

300 E Royal Lane Ste # 100, Irving, TX 75039

Desk: Ext:115

Mail:

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About AB Technologies Inc.