Delta System & Software, Inc.
AI/ML Engineer ( US Citizen)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer with 4-7 years of experience, a Master’s degree in a quantitative field, expertise in Python and ML libraries, and strong cloud deployment skills. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 18, 2025
🕒 - 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
United States
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Azure #Python #Libraries #ML (Machine Learning) #PyTorch #Cloud #MLflow #Computer Science #Data Science #AWS (Amazon Web Services) #GCP (Google Cloud Platform) #API (Application Programming Interface) #TensorFlow
Role description
Required Qualifications
• Experience: 4-7 years of professional experience in Machine Learning Engineering, AI Development, or a closely related field.
• Education: Master’s degree in Computer Science, Data Science, Engineering, or a quantitative field.
• Technical Proficiency:
◦ Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn).
◦ Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure).
◦ Deep understanding of the architecture and fine-tuning of Large Language Models.
• Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow) and validation frameworks (e.g., DeepEval).
• Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions.
⭐ Preferred Qualifications
• Hands-on experience developing applications or services using Google's Gemini API or models.
• Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock.
• Experience in building and managing multi-step, reasoning-based Agentic AI systems.
• Prior experience in optimizing models for latency and cost efficiency in a production environment.
Required Qualifications
• Experience: 4-7 years of professional experience in Machine Learning Engineering, AI Development, or a closely related field.
• Education: Master’s degree in Computer Science, Data Science, Engineering, or a quantitative field.
• Technical Proficiency:
◦ Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn).
◦ Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure).
◦ Deep understanding of the architecture and fine-tuning of Large Language Models.
• Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow) and validation frameworks (e.g., DeepEval).
• Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions.
⭐ Preferred Qualifications
• Hands-on experience developing applications or services using Google's Gemini API or models.
• Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock.
• Experience in building and managing multi-step, reasoning-based Agentic AI systems.
• Prior experience in optimizing models for latency and cost efficiency in a production environment.
