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Lead AI ML Engineer Jobs

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Business Development Representative
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United States , Mountain View
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80000.00 - 100000.00 USD / Year
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Inworld AI
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Architect 4, Software Architecture
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United States , Remote
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90695.14 - 212566.73 USD / Year
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Comcast Advertising
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Senior AI Engineer
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Turkey , Istanbul
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DefineX
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Principal Site Reliability Engineer (AI-first SRE)
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Groupon
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Head of Quality, AI Business
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United Kingdom
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Prolific
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Director, Machine Learning Platform
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Spain , Barcelona
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Delivery Hero
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Head of Quality, AI Business
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Mexico , Mexico City
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Senior Staff Machine Learning Engineer
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United States , New York
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264641.00 - 378058.00 USD / Year
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Spotify
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Staff LLM Engineer
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Argentina , Buenos Aires
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GoFundMe
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Technology Lead – AI/ML & GenAI
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United Arab Emirates , Abu Dhabi
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NorthBay
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Enterprise Architect
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United Arab Emirates , Abu Dhabi
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NorthBay
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Enterprise Architect
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United Arab Emirates , Abu Dhabi
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NorthBay
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Enterprise Architect – GenAI
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United Arab Emirates , Abu Dhabi
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NorthBay
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Technology Lead – AI/ML & GenAI
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United Arab Emirates , Abu Dhabi
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NorthBay
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Technology Lead – AI/ML & GenAI
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United Arab Emirates , Abu Dhabi
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NorthBay
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Senior Machine Learning Engineer - Multimodal - AI Teams
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France , Paris
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Doctolib
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Senior Expert for Industry Foundation Models
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Germany , Munich
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BMW
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Snowflake Solutions Engineer
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United States , Easton
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Victaulic
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Senior Frontend Engineer
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NorthBay
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Principal Data Scientist
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United States , Bellevue
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127400.00 - 229800.00 USD / Year
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T-Mobile
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Lead AI ML Engineer jobs represent the pinnacle of technical leadership in one of the most dynamic fields of technology. Professionals in these roles are the strategic architects and hands-on builders of intelligent systems, responsible for guiding the entire lifecycle of artificial intelligence and machine learning solutions from conception to deployment. They bridge the gap between advanced theoretical research and robust, scalable production applications, ensuring that AI delivers tangible business value. Typically, a Lead AI ML Engineer oversees the design, development, and implementation of sophisticated AI/ML models to solve complex, high-impact business challenges. Common responsibilities include leading a team of data scientists and engineers, setting technical direction, and making pivotal architectural decisions. They are deeply involved in hands-on coding, utilizing frameworks like TensorFlow and PyTorch to build models for areas such as Natural Language Processing (NLP), including work with Large Language Models (LLMs) and Generative AI, computer vision, recommendation systems, and predictive analytics. A critical aspect of the role is establishing and championing MLOps practices—creating automated pipelines for continuous integration, delivery, and monitoring of models to ensure they remain performant and reliable in live environments. Collaboration is key; they work closely with product managers, software engineers, and business stakeholders to integrate AI capabilities seamlessly into products and services. The typical skill set for these senior positions is extensive. A strong foundation in programming, primarily Python, is essential, along with deep expertise in machine learning algorithms, statistics, and data structures. Experience with cloud platforms (AWS, GCP, Azure) and big data technologies is often required to handle large-scale data processing. Beyond technical prowess, successful Lead AI ML Engineers possess exceptional problem-solving abilities, strategic thinking, and clear communication skills to explain complex concepts to non-technical audiences. Leadership and mentorship are fundamental, as they are expected to grow and guide their teams. Most roles require substantial professional experience, often 7+ years in software engineering with a significant portion dedicated to AI/ML, including proven experience in deploying models to production. For seasoned professionals seeking to shape the future of technology, Lead AI ML Engineer jobs offer the opportunity to drive innovation, lead talented teams, and build the intelligent systems that define the next generation of digital products. This career path is ideal for those who excel at translating cutting-edge research into reliable, scalable solutions that solve real-world problems.

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