

Insight Global
Senior Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer with 10+ years of experience in AWS ML Infrastructure. Contract length is 18-24 months, remote work in CST. Key skills include SQL, AWS S3, Spark, and building ML pipelines. Master’s or PhD required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
720
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🗓️ - Date
July 8, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Chicago, IL
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🧠 - Skills detailed
#AWS Machine Learning #Snowflake #Data Processing #Recommender Systems #S3 (Amazon Simple Storage Service) #AWS S3 (Amazon Simple Storage Service) #Spark (Apache Spark) #SQL Queries #ML (Machine Learning) #AWS (Amazon Web Services) #Python #Pandas #SQL (Structured Query Language)
Role description
Senior AWS Machine Learning Engineer
18-24 month contract + extensions, possibility to go permanent in the future
Remote- working hours in CST
Requirements:
- 10+ years with expertise as a Machine Learning Engineer on the ML Infrastructure/ML System side in AWS (back end engineer)
- SQL, experience using SQL platforms and writing SQL queries
- AWS - Processing data using AWS S3 and Spark or Python Pandas
- Know the difference between page data and streaming data processing - Build high performing APIs
- Build systems that read and convert data into inputs to ML models
- Build software systems used to train and evaluate ML models all within AWS
- Ability to give examples around things they have built ML pipelines such as: services, search systems, recommender systems, fraud detection.
- Master’s in Applied Science or PHD in Applied Science
Plus:
- Snowflake
- Exposure to Applied Science work
D2D:
This global hotel company is looking for a very skilled Machine Learning Engineer on the Systems/Back end/Infrastructure side. This ML Engineer will build software which uses machine learning on a typical back end application. They will build the following: high performance APIs, systems that read and convert data to inputs to ML models, and software systems used to train and evaluate ML. We need someone who has done some of the following: built ML pipelines, services, search systems, recommender systems, fraud detection. Project examples could be:
- Specific projects the team is working on: feature store database used to store data being use by ML models (if you go to Amazon, they know who you are, they know our profile, our purchases, compare to people in similar geographic regions using an array of data by feeding your amazon login and retrieve data representing your profile). (Feature Store Rebuild)
- To make models useful, you have to train them through big amounts of data. There are dozens of these models and simplify the data to be used by the models.
- Search on the website, recommender systems. Create elements of search engines.
Senior AWS Machine Learning Engineer
18-24 month contract + extensions, possibility to go permanent in the future
Remote- working hours in CST
Requirements:
- 10+ years with expertise as a Machine Learning Engineer on the ML Infrastructure/ML System side in AWS (back end engineer)
- SQL, experience using SQL platforms and writing SQL queries
- AWS - Processing data using AWS S3 and Spark or Python Pandas
- Know the difference between page data and streaming data processing - Build high performing APIs
- Build systems that read and convert data into inputs to ML models
- Build software systems used to train and evaluate ML models all within AWS
- Ability to give examples around things they have built ML pipelines such as: services, search systems, recommender systems, fraud detection.
- Master’s in Applied Science or PHD in Applied Science
Plus:
- Snowflake
- Exposure to Applied Science work
D2D:
This global hotel company is looking for a very skilled Machine Learning Engineer on the Systems/Back end/Infrastructure side. This ML Engineer will build software which uses machine learning on a typical back end application. They will build the following: high performance APIs, systems that read and convert data to inputs to ML models, and software systems used to train and evaluate ML. We need someone who has done some of the following: built ML pipelines, services, search systems, recommender systems, fraud detection. Project examples could be:
- Specific projects the team is working on: feature store database used to store data being use by ML models (if you go to Amazon, they know who you are, they know our profile, our purchases, compare to people in similar geographic regions using an array of data by feeding your amazon login and retrieve data representing your profile). (Feature Store Rebuild)
- To make models useful, you have to train them through big amounts of data. There are dozens of these models and simplify the data to be used by the models.
- Search on the website, recommender systems. Create elements of search engines.




