MLOps Engineer(NJ)
Company shown to members 🔒 · Remote · US only
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First recorded by Psst: 14 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- 5+ years required
- Where you can live
- US only
- Skills and tools
- oracle, python, aws, docker, kubernetes, terraform
- Degree or licence
- Mentioned (bachelor's)
- Job type
- Full-time
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Job details
- Where you can work
- United States
- Employment type
- Full-time
- Advertised pay
- Not stated by the employer
- Experience
- 5+ years required
- Employer publication date
- 26 October 2022
- First recorded by Psst
- 14 October 2026
- Last checked at the source
- 10 November 2026
About the job
The company the company is looking for experienced Machine Learning Engineers to join our fast-growing advanced the company consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted the company 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 the company 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.
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