Tiger Analytics

Delivers Data and AI transformation

Machine Learning Operations Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

A bachelor's degree or higher in computer science or a related field, plus at least five 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 with AWS SageMaker, including ProcessingJobs, TrainingModels, and EndPoints.
Experience with Lambda, CloudFormation or Terraform, Apache Airflow, Astronomer, and Docker.
Knowledge of traditional machine-learning models.
Experience with Python, Spark, Hadoop, and Docker, emphasizing good coding practices in a continuous-integration context, model evaluation, and experimental design.
Knowledge of machine-learning frameworks including scikit-learn, TensorFlow, and Keras.
Experience with Pandas, scikit-learn, NumPy, and SciPy.
Knowledge of database and data engineering.
Experience with Oracle, Spark, Hadoop, Athena, API, FastAPI, Flask, and REST.
Knowledge of MLflow, Airflow, and Kubernetes.
Experience with cloud environments and knowledge of AWS services, Service Catalog, SNS, and SES.

Responsibilities

Build, deploy, test, and monitor model-training pipelines using AWS SageMaker, AWS CloudFormation, AWS CodePipeline, Lambda, and related tools.
Develop Airflow DAGs to run training and scoring pipelines.
Develop a testing framework with Pytest.
Implement a monitoring solution using a custom solution with Lambda and Dash.
Develop data-quality solutions, potentially leveraging Great Expectations.

MLOps Engineer(NJ)

Tiger Analytics Inc. · United States (Remote) · Full-time · Posted 2022-10-26

Workplace: remote

Department: MLE

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.

Apply

Apply at Tiger Analytics Inc.

About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size: 1,001-5,000
Company stage: Not listed
Total funding: Not listed
Headquarters: San Jose, CA
Founded: 2010

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