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Machine Learning Team Lead Jobs (Hybrid work)

263 Job Offers

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Senior Data Scientist
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United States , Dallas
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173400.00 - 234600.00 USD / Year
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Boeing
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Machine Learning Engineer - AI Assistant + Autonomous AI Agents
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United States , San Francisco Bay Area
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240000.00 - 300000.00 USD / Year
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Glean
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Senior LLM Engineer
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Argentina , Buenos Aires
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GoFundMe
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Vice President Data Product Owner
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India , Pune
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Barclays
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Junior Data Scientist
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United States , San Francisco
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70000.00 - 95000.00 USD / Year
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Aramark
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Product Design Director
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United Kingdom , London
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AKQA
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Product Design Director
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United Kingdom , London
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AKQA
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Product Design Director
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United Kingdom , London
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AKQA
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Ai Architect
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Turkey , Istanbul
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Zoolatech
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AI Product Manager
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Turkey , Istanbul
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Zoolatech
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Senior Data Scientist, Product
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United States , Menlo Park
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179000.00 - 210000.00 USD / Year
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Robinhood
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Sr. Product Manager - AI
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India , Hyderabad
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Highspot
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Solutions Engineer
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United Kingdom , London
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Encord
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Data Science Manager
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France , Paris
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Artelys
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Product Design Director
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United Kingdom , London
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Business Process Manager
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India , Bangalore
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Business Development Manager
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Poland , Warsaw
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Inetum
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Data Science and AI Expert
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Belgium , Brussels
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Sopra Steria
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Senior Data Science Analyst
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India , Chennai
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Citi
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Staff Product Manager, Data Platform
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United States , San Francisco
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207000.00 - 244000.00 USD / Year
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Explore the pivotal role of a Machine Learning Team Lead and discover the exciting career opportunities available in this high-impact field. Machine Learning Team Lead jobs represent a unique convergence of deep technical expertise and visionary leadership, sitting at the heart of where innovative AI strategy meets execution. Professionals in this role are responsible for guiding a team of machine learning scientists and engineers to transform complex business objectives into tangible, scalable AI solutions. They are the crucial bridge between executive vision, cross-functional stakeholders, and the technical team, ensuring that machine learning initiatives deliver measurable value. The core responsibilities of a Machine Learning Team Lead are dual-faceted, encompassing both people leadership and technical stewardship. On the leadership front, they are tasked with building, mentoring, and motivating a high-performing team. This involves fostering a culture of innovation and psychological safety, facilitating professional growth, managing workloads, and delegating tasks effectively. They orchestrate the team’s internal dynamics and champion their work externally. Technically, they provide strategic direction, define the team’s roadmap, and oversee the end-to-end development lifecycle of machine learning models—from research and prototyping to deployment and monitoring. They ensure scientific rigor and operational excellence, making critical architectural decisions and balancing ambitious research with robust, production-ready engineering. Typical requirements and skills for these leadership positions are comprehensive. A strong academic background in a quantitative field such as Computer Science, Statistics, or Machine Learning is often expected, frequently accompanied by an advanced degree (MS or PhD) or equivalent industry experience. Candidates must possess a profound, hands-on understanding of machine learning theory, modern software development practices (including MLOps), and cloud computing platforms. Beyond technical prowess, exceptional soft skills are non-negotiable: outstanding communication to translate complex concepts for diverse audiences, proven experience in project management and agile methodologies, and a genuine passion for coaching and developing talent. Successful leads demonstrate strategic thinking, an ability to manage stakeholder expectations, and a knack for prioritizing initiatives that maximize team impact. For those seeking Machine Learning Team Lead jobs, the role offers the challenge of driving the AI frontier while shaping the next generation of talent. It is a career path for those who excel at solving multifaceted problems, inspiring teams, and turning cutting-edge research into real-world applications that define the future of technology.

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