SIXT
mobility service provider
EngineeringManager(m/f/d)MachineLearning
Neural analysis suggests this role is
optimal for mid candidates.
“Engineering Manager (m/f/d) Machine Learning at SIXT. Skills: Machine Learning Engineering, MLOps, Cloud Expertise (AWS), Team Leadership, Technical Strategy. Lead and scale the Machine Learning Engineering team. Partner with data scientists to transform models into production-grade ML applications on the central MLOps platform”
What You'll Achieve.
Transform models into production-grade ML applications; Enable data scientists to build scalable, maintainable ML solutions; Ensure alignment with business objectives; Build high-performing teams
Industry & Context.
What They're Looking For.
Must Have
Proven leadership experience with 3+ years managing machine learning or software engineering teams, Strategic technical vision with experience leading complex, multi-stakeholder ML/data science initiatives from concept to production, Deep ML and cloud expertise including hands-on experience with machine learning frameworks, MLOps practices, and AWS cloud services, Production ML deployment experience with real-world examples of deploying and maintaining large-scale ML systems in production environments, Exceptional communication skills, Ability to translate between technical and business stakeholders, Talent for building consensus across diverse teams, Hands-on technical credibility with the ability to review architectures, guide technical decisions, and occasionally contribute to critical implementations
Nice to Have
Ideally across multiple locations, Experience building high-performing teams, Experience bridging platform and practice by translating MLOps platform capabilities into practical guidance for data science teams, while channeling ML engineering requirements back to the MLOps platform team
What You'll Do.
Lead and scale the Machine Learning Engineering team
Partner with data scientists to transform models into production-grade ML applications on the central MLOps platform
Shape ML Engineering standards by establishing best practices
and quality benchmarks
Drive technical strategy and architecture across data science
and engineering teams
Communicate system designs to tech leadership
Translate MLOps platform capabilities into practical guidance for data science teams
Channel ML engineering requirements back to the MLOps platform team
Foster collaboration and excellence
Build relationships across cross-functional teams
Create a culture of innovation and continuous improvement
Guide technical decisions
Occasionally contribute to critical implementations
How You'll Work.
Team & Collaboration
Partner with data scientists; Collaborate with data science, MLOps, and engineering teams; Build relationships across cross-functional teams; Communicate system designs to tech leadership; Channel ML engineering requirements back to the MLOps platform team
Communication Scope
Exceptional communication skills; Ability to translate between technical and business stakeholders; Talent for building consensus across diverse teams
Process & Methodology
Leading complex, multi-stakeholder ML/data science initiatives from concept to production
Full Job Description
Our vision is: Transform the world moves, because people expect better. Join our Data Science organization and make the magic happen. We drive business processes like pricing and many more with the use of sophisticated algorithms and building highly scaling algorithms. Apply now and be part of our journey. YOUR ROLE AT SIXT * You will lead and scale our Machine Learning Engineering team that partners with data scientists to transform models into production-grade ML applications on our central MLOps platform * You will shape ML Engineering standards by establishing best practices, design patterns, and quality benchmarks that enable data scientists to build scalable, maintainable ML solutions * You will drive technical strategy and architecture across data science, MLOps, and engineering teams, ensuring alignment with business objectives and communicating system designs to tech leadership * You will bridge platform and practice by translating MLOps platform capabilities into practical guidance for data science teams, while channeling ML engineering requirements back to the MLOps platform team * You will foster collaboration and excellence by building strong relationships across cross-functional teams, mentoring engineers, and creating a culture of innovation and continuous improvement YOUR SKILLS MATTER * Proven leadership experience with 3+ years managing machine learning or software engineering teams, ideally across multiple locations, with a track record of building high-performing teams * Strategic technical vision with experience leading complex, multi-stakeholder ML/data science initiatives from concept to production * Deep ML and cloud expertise including hands-on experience with machine learning frameworks, MLOps practices, and AWS cloud services * Production ML deployment experience with real-world examples of deploying and maintaining large-scale ML systems in production environments * Bridge-builder mindset with exceptional communication skills, ability to
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