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MLOps Engineer(NJ)

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

United States

Offer summary

Qualifications:

Bachelor's degree in computer science or a related field and 5+ years of experience, Experience working with AWS SageMaker, Lambda, Apache Airflow, Docker, and ML frameworks such as Tensorflow and Keras.

Key responsabilities:

Building and deploying ML models, creating and monitoring pipelines, developing data quality solutions
Collaborating with Data Engineers and Data Scientists to build data and model pipelines, conducting ML tests and experiments

Tiger Analytics XLarge https://www.tigeranalytics.com/

1001 - 5000 Employees

See more Tiger Analytics offers

Job description

Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. 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.