Insight Global

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include Python programming, SQL, and experience with LLMs and cloud platforms like AWS or Azure. A Bachelor's Degree is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
560
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🗓️ - Date
July 18, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Databricks #SQL (Structured Query Language) #Data Cleansing #Databases #ML (Machine Learning) #ChatGPT #AWS (Amazon Web Services) #Monitoring #Project Management #Snowflake #Python #Deployment #Cloud #Programming #AI (Artificial Intelligence) #Azure #Scala
Role description
Required Skills & Experience • Prior experience working with Machine Learning and/or AI technologies • Experience leveraging Large Language Models (LLMs) such as Claude, ChatGPT, or similar tools to accelerate development, automate tasks, and generate code solutions • Ability to effectively prompt AI tools to create, troubleshoot, or enhance Python programs and workflows • Experience with cloud-based platforms and environments such as Snowflake, Databricks, Azure, or AWS (familiarity with cloud compute resources and cloud-based databases) • Strong SQL skills for data querying and analysis • Proficiency in Python programming • Bachelor's Degree required Nice to Have Skills & Experience • End-to-end machine learning model development and deployment experience Job Description • Partner closely with the Data Analytics and Engineering teams to design, build, deploy, and support machine learning solutions that drive business outcomes • Assist in developing and maintaining the infrastructure required to support machine learning models, including deployment, monitoring, and ongoing performance evaluation • Write and maintain Python-based code to support AI and machine learning initiatives, with a strong emphasis on hands-on development and execution • Support the machine learning lifecycle through data preparation activities, including data cleansing, organization, labeling, and validation • Analyze model performance, identify improvement opportunities, and help optimize solutions for scalability and effectiveness in production environments • Work with structured and unstructured data using SQL, cloud platforms, and related technologies to support model development and deployment efforts • Collaborate across multiple phases of the machine learning process, requiring strong organization, attention to detail, and project management skills • Contribute to machine learning initiatives by supporting key components of the model development lifecycle, rather than being solely responsible for building solutions entirely from scratch • Leverage AI tools and Large Language Models (LLMs) to improve development efficiency, automate tasks, and accelerate solution delivery