

Artmac
Senior Data Scientist - Generative AI & Agentic Systems
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist specializing in Generative AI & Agentic Systems, requiring 8-15 years of experience, with a pay rate of "unknown" for a contract length of "unknown," located in San Jose, California. Key skills include Deep Learning, TensorFlow, and cloud AI platforms.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
October 1, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
San Jose, CA
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🧠 - Skills detailed
#AWS SageMaker #Langchain #SQL (Structured Query Language) #Hugging Face #Python #Monitoring #Data Science #Cloud #Automation #Consulting #Deep Learning #PyTorch #AWS (Amazon Web Services) #Transformers #Azure #Leadership #ML (Machine Learning) #"ETL (Extract #Transform #Load)" #Deployment #GCP (Google Cloud Platform) #Reinforcement Learning #ML Ops (Machine Learning Operations) #MLflow #AI (Artificial Intelligence) #TensorFlow #SageMaker
Role description
Who We Are
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to customers.
Job Description
Job Title : Senior Data Scientist – Generative AI & Agentic Systems
Job Type : W2/C2C
Experience : 8 – 15 years
Location : San Jose, California
Responsibilities
• 8–15 years of experience in Machine Learning / AI / Data Science with strong hands-on expertise in Deep Learning & Generative AI.
• Proven experience with TensorFlow, PyTorch, Hugging Face, LangChain, or LlamaIndex.
• Strong knowledge of LLMs (Large Language Models), Transformers, Diffusion Models, and Reinforcement Learning.
• Expertise in building and deploying agentic AI systems for automation and reasoning.
• Proficiency in Python, SQL, and ML Ops pipelines (e.g., Kubeflow, MLflow, Weights & Biases).
• Strong experience with cloud AI platforms (AWS Sagemaker, GCP Vertex AI, Azure ML).
• Design, develop, and deploy advanced Deep Learning and Generative AI models for real-world applications.
• Build and optimize agentic AI systems capable of autonomous reasoning, planning, and decision-making.
• Conduct research and experimentation to evaluate emerging AI/ML methodologies and integrate them into production.
• Collaborate with product, engineering, and research teams to translate business challenges into AI-driven solutions.
• Drive end-to-end model lifecycle management – data preparation, feature engineering, training, evaluation, deployment, and monitoring.
• Contribute to open-source projects, publications, and technical thought leadership.
Qualification
• Bachelor's degree or equivalent combination of education and experience.
Who We Are
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to customers.
Job Description
Job Title : Senior Data Scientist – Generative AI & Agentic Systems
Job Type : W2/C2C
Experience : 8 – 15 years
Location : San Jose, California
Responsibilities
• 8–15 years of experience in Machine Learning / AI / Data Science with strong hands-on expertise in Deep Learning & Generative AI.
• Proven experience with TensorFlow, PyTorch, Hugging Face, LangChain, or LlamaIndex.
• Strong knowledge of LLMs (Large Language Models), Transformers, Diffusion Models, and Reinforcement Learning.
• Expertise in building and deploying agentic AI systems for automation and reasoning.
• Proficiency in Python, SQL, and ML Ops pipelines (e.g., Kubeflow, MLflow, Weights & Biases).
• Strong experience with cloud AI platforms (AWS Sagemaker, GCP Vertex AI, Azure ML).
• Design, develop, and deploy advanced Deep Learning and Generative AI models for real-world applications.
• Build and optimize agentic AI systems capable of autonomous reasoning, planning, and decision-making.
• Conduct research and experimentation to evaluate emerging AI/ML methodologies and integrate them into production.
• Collaborate with product, engineering, and research teams to translate business challenges into AI-driven solutions.
• Drive end-to-end model lifecycle management – data preparation, feature engineering, training, evaluation, deployment, and monitoring.
• Contribute to open-source projects, publications, and technical thought leadership.
Qualification
• Bachelor's degree or equivalent combination of education and experience.