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Senior Engineering Manager - AI/ML United States, Austin Jobs

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Senior Machine Learning Engineering Manager
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Lead a core ML team at Atlassian, building advanced AI/ML models for revenue and forecasting. You'll manage the full ML lifecycle, from research to deployment, using cutting-edge techniques. Requires 5+ years managing ML engineering teams and a quantitative Master's/PhD. Role based in Seattle, Au...
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United States , Seattle; Austin; New York; Washington DC
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190300.00 - 305600.00 USD / Year
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Atlassian
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Until further notice
Senior Software QA Engineer Manager
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Lead QA strategy and automation as a Senior Software QA Engineer Manager in Austin. You will standardize processes, mentor a top-tier team, and partner with cross-functional leaders to ensure flawless, high-speed releases. This role requires 8+ years in QA with strong automation and leadership ex...
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United States , Austin
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Not provided
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dynaConnections
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Until further notice
A Senior Engineering Manager in AI/ML is a pivotal leadership role at the intersection of cutting-edge technology, strategic vision, and people management. This professional is responsible for guiding and scaling teams of data scientists, machine learning engineers, and software developers to conceptualize, build, and deploy intelligent systems that solve complex business problems. For those seeking senior engineering manager AI/ML jobs, this position represents the apex of technical leadership, requiring a balance of deep technical expertise in artificial intelligence and proven managerial acumen. Typically, individuals in this role oversee the entire AI/ML product development lifecycle. Common responsibilities include defining the technical vision and roadmap for AI initiatives, aligning these projects with overarching business goals, and securing necessary resources. They are accountable for the quality, scalability, and reliability of machine learning models and the platforms that serve them. A significant part of their day involves mentoring team leads and senior individual contributors, fostering a culture of innovation, rigorous experimentation, and continuous learning. They also act as a crucial bridge, translating complex technical concepts for non-technical stakeholders and advocating for data-driven decision-making at the executive level. The skill set for these leadership jobs is multifaceted. A strong foundation in machine learning concepts, algorithms, and modern software engineering practices (like MLOps) is essential to earn technical credibility and guide architectural decisions. Equally important are exceptional people management skills: the ability to recruit top talent, manage performance, and cultivate high-performing, collaborative teams. Senior Engineering Managers in this field must possess strategic program management capabilities to prioritize projects, manage timelines, and navigate trade-offs between research, development, and production deployment. They require excellent communication skills to collaborate with product management, data engineering, and infrastructure teams. Typical requirements for senior engineering manager AI/ML jobs often include an advanced degree (Master's or PhD) in Computer Science, Statistics, or a related quantitative field, coupled with 8+ years of industry experience, including at least 3-5 years in a hands-on technical leadership or management role directly within AI/ML. Proven experience in shipping and maintaining large-scale machine learning systems in production is a key differentiator. This career path is ideal for those passionate about leading at the forefront of technological innovation, shaping the future of intelligent applications, and driving tangible business impact through artificial intelligence.

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