New York Technology Partners
Lead AI/ML Engineer-Local to Redmond WA
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead AI/ML Engineer in Redmond, WA, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, TensorFlow/PyTorch, MLOps, and experience with LLMs. Leadership experience is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 13, 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
Redmond, WA
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🧠 - Skills detailed
#Deployment #Cloud #Compliance #ML (Machine Learning) #SageMaker #Leadership #Data Engineering #Databases #PyTorch #Scala #ML Ops (Machine Learning Operations) #TensorFlow #Kubernetes #Strategy #AWS SageMaker #MLflow #Airflow #GCP (Google Cloud Platform) #AWS (Amazon Web Services) #Azure #"ETL (Extract #Transform #Load)" #Python #Docker #AI (Artificial Intelligence) #Security #Monitoring #Transformers
Role description
Key Responsibilities
• Define and implement AI/ML architecture, frameworks, and standards.
• Lead end-to-end model lifecycle—data prep, training, deployment, and monitoring.
• Build scalable ML Ops pipelines and reusable components.
• Mentor senior engineers and guide cross-functional teams.
• Drive adoption of Generative AI, LLMs, and advanced ML techniques.
• Ensure compliance with AI governance, fairness, and security principles.
• Partner with business and product leaders to align AI strategy with outcomes.
Required Skills & Experience
• Strong expertise in Python, TensorFlow/PyTorch, Scikit-learn, Transformers.
• Proficient in MLOps (MLflow, Airflow, Docker, Kubernetes) and cloud AI platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
• Experience in LLM fine-tuning, RAG, and vector databases (FAISS/Pinecone).
• Deep understanding of data engineering, model governance, and AI ethics.
• Excellent leadership, communication, and stakeholder management skills.
Key Responsibilities
• Define and implement AI/ML architecture, frameworks, and standards.
• Lead end-to-end model lifecycle—data prep, training, deployment, and monitoring.
• Build scalable ML Ops pipelines and reusable components.
• Mentor senior engineers and guide cross-functional teams.
• Drive adoption of Generative AI, LLMs, and advanced ML techniques.
• Ensure compliance with AI governance, fairness, and security principles.
• Partner with business and product leaders to align AI strategy with outcomes.
Required Skills & Experience
• Strong expertise in Python, TensorFlow/PyTorch, Scikit-learn, Transformers.
• Proficient in MLOps (MLflow, Airflow, Docker, Kubernetes) and cloud AI platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
• Experience in LLM fine-tuning, RAG, and vector databases (FAISS/Pinecone).
• Deep understanding of data engineering, model governance, and AI ethics.
• Excellent leadership, communication, and stakeholder management skills.
