Tiger Analytics

MLOps Engineer(NJ)

Tiger Analytics • $100K — $140K *
US-AnywhereRemote in New Jersey, US
Information Technology
5 - 7 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Bachelor's degree in computer science or related field
  • 5+ years of IT experience, specifically in machine learning
  • Proficient in AWS services, particularly SageMaker
  • Experience with pipeline orchestration tools like Airflow
  • Strong coding skills in Python, Spark, and Docker
  • Familiarity with ML frameworks such as Scikit-learn and Tensorflow
  • Knowledge of data engineering principles

Responsibilities

  • Lead the development of machine learning pipelines from training to deployment
  • Create and implement testing frameworks using Pytest
  • Monitor ML models and pipelines with custom solutions
  • Develop and maintain Airflow DAGs for automated workflows
  • Build data quality solutions, leveraging tools like Great Expectations
  • Collaborate with data engineers and scientists for pipeline efficiency
  • Utilize AWS services for managing ML jobs and infrastructure

Benefits

  • Significant career development opportunities
  • Engaged in a fast-growing, entrepreneurial environment
  • High degree of individual responsibility on projects
Full Job Description
You will be responsible for:
  • ML Engineer with 5-7 years of IT experience.
  • Pipeline Training Models, Building, Deployment, Testing, and Monitoring using AWS SageMaker, AWS CFT, AWS CodePipeline, Lambda, etc.
  • Develop Airflow DAGs to run training and scoring pipelines
  • Develop a Testing framework with Pytest
  • Implement monitoring solution with homebrew solution using Lambda and Dash
  • Develop Data Quality solutions potentially leveraging Great Expectations.

Requirements
  • Bachelor's degree or higher in computer science or related, with 5+ years of work experience
  • Ability to collaborate with Data Engineers and Data Scientists to build data and model pipelines and help run machine learning tests and experiments
  • Experience in AWS - SageMaker (ProcessingJobs, TrainingModels, EndPoints)
  • Experience in Lambda CloudFormation or Terraform Apache Airflow, Astronomer Docker
  • Knowledge of traditional ML Models.
  • Python, Spark, Hadoop, and Docker with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
  • Knowledge of ML frameworks like Scikitlearn, Tensorflow, and Keras.
  • Experience in Pandas, sklearn, Numpy, Scipy

Additional Skills Required
  • Knowledge of Database/Data Engineering.
  • Experience with Oracle, Spark, Hadoop, Athena, API, FastAPI, Flask, ReST
  • Knowledge of MLflow, Airflow, and Kubernetes
  • Experience with Cloud environments and knowledge of AWS Services, Service Catalog, SNS, SES

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

About Tiger Analytics

Tiger Analytics is a consulting firm that provides data analytics consulting services to businesses. The company specializes in data science, machine learning, and artificial intelligence. Tiger Analytics helps businesses to leverage data to make better decisions, improve operations, and drive growth. The company has worked with clients in a variety of industries, including healthcare, retail, finance, and technology.
Learn more about Tiger Analytics
Size
500 employees
Industry
Information Technology
Net Income
$1 million
Founded
2011
5 Year Trend
+50%
Revenue
$10 million
* Ladders Estimates

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