

Gardner Resources Consulting, LLC
Machine Learning Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer with a contract length of "unknown" and a pay rate of "unknown". Key skills include Python, ML and AI expertise, LLM development, and experience in IAM or Cybersecurity is preferred.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
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ποΈ - Date
January 30, 2026
π - Duration
Unknown
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ποΈ - Location
Unknown
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π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
San Jose, CA
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π§ - Skills detailed
#GCP (Google Cloud Platform) #Automation #ML (Machine Learning) #Data Science #Cloud #Security #TensorFlow #AI (Artificial Intelligence) #Deployment #IAM (Identity and Access Management) #Cybersecurity #Public Cloud #Python #Model Evaluation #PyTorch #Scala #NLP (Natural Language Processing)
Role description
Job Details
Weβre seeking a Machine Learning Engineer to design and implement scalable AI/ML solutions that drive product innovation and business insights. This role partners closely with data scientists, software engineers, and product managers to bring ML capabilities into production.
Projects: This role focuses on applying machine learning and LLMs to enhance IAM decision-making and automation. Engineers will build, train, and integrate LLM-based models that support access, risk evaluation, and governance use cases across internal IAM products. The environment is highly product-focused and supports advanced AI/ML-powered decisioning as part of IAM processes.
Responsibilities
β’ Design, build, and deploy ML applications and pipelines on GCP.
β’ Develop and integrate ML and NLP/SLM solutions, including fine-tuning and production hosting.
β’ Collaborate cross-functionally to deliver scalable, high-performance ML systems.
β’ Support the full machine learning lifecycle from data preparation through model evaluation and deployment.
Required Qualifications
β’ 5+ years of experience as a ML Engineer; Strong proficiency in Python
β’ Experience with ML and AI, including LLM development and integration
β’ Experience deploying and operating ML models in production environments
β’ Hands-on experience building data-driven decision systems embedded in product workflows
β’ Experience integrating ML models via APIs into internal platforms
β’ Strong understanding of ML workflows, feature engineering, and model evaluation
β’ Experience with common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
β’ Familiarity with hybrid cloud environments (public cloud and proprietary private cloud)
Preferred / Nice to Have
β’ Experience in Identity & Access Management (IAM) or Cybersecurity
Job Details
Weβre seeking a Machine Learning Engineer to design and implement scalable AI/ML solutions that drive product innovation and business insights. This role partners closely with data scientists, software engineers, and product managers to bring ML capabilities into production.
Projects: This role focuses on applying machine learning and LLMs to enhance IAM decision-making and automation. Engineers will build, train, and integrate LLM-based models that support access, risk evaluation, and governance use cases across internal IAM products. The environment is highly product-focused and supports advanced AI/ML-powered decisioning as part of IAM processes.
Responsibilities
β’ Design, build, and deploy ML applications and pipelines on GCP.
β’ Develop and integrate ML and NLP/SLM solutions, including fine-tuning and production hosting.
β’ Collaborate cross-functionally to deliver scalable, high-performance ML systems.
β’ Support the full machine learning lifecycle from data preparation through model evaluation and deployment.
Required Qualifications
β’ 5+ years of experience as a ML Engineer; Strong proficiency in Python
β’ Experience with ML and AI, including LLM development and integration
β’ Experience deploying and operating ML models in production environments
β’ Hands-on experience building data-driven decision systems embedded in product workflows
β’ Experience integrating ML models via APIs into internal platforms
β’ Strong understanding of ML workflows, feature engineering, and model evaluation
β’ Experience with common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
β’ Familiarity with hybrid cloud environments (public cloud and proprietary private cloud)
Preferred / Nice to Have
β’ Experience in Identity & Access Management (IAM) or Cybersecurity






