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Machine Learning Team Lead Jobs

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It Solution Architect
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United Kingdom , London
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BDO UK LLP
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Data Scientist / AI Solution Architect
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35.00 EUR / Hour
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Sigli
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Sr. Backend Software Engineer
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India , Pune
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Addepar
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Principal Applied Scientist - ZMS
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Germany , Berlin
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Zalando Lounge
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Artificial Intelligence (AI) Lead
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India , Noida
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Taazaa Inc
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Software Engineer
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United States
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Ocean Blue Solutions
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Principal Applied Scientist - ZMS
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Germany , Berlin
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Zalando Sverige
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Head of Quality, AI Business
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Mexico , Mexico City
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Prolific
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Business Development Manager
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India , Navi Mumbai
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Percivon
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Lab Systems & Data Lead
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Belgium , Beerse, Antwerp
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myGwork - LGBTQ+ Business Community
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Senior Software Engineer, Forward Deployed
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United States , Washington DC–Baltimore
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164000.00 - 240000.00 USD / Year
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Invisible Technologies
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R&D Engineering Group Manager
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United Kingdom , Dundee
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Optimove
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Ai Product Designer
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IQM Corporation
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Principal Applied Scientist
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Germany , Berlin
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Zalando Sverige
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Staff AI Architect
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United States
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193800.00 - 227700.00 USD / Year
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Confluent
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Client Manager
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United States , Lafayette
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62000.00 - 88000.00 USD / Year
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Recruitics
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Machine Operator-Fabricator
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United States , Tolleson
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Nesco Resource
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Product Manager - Risk and Compliance
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Bulgaria , Sofia; Varna
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myPOS
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Principal Architect, Payment & Fraud Systems
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United States , Bellevue; Atlanta
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123800.00 - 223300.00 USD / Year
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T-Mobile
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Enterprise Architect
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United States , Littleton
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Robert Half
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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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