Machine Learning Lead

1 month ago


Prague, Czech Republic Deloitte Full time

🎯 What we expect from you 🎯

  • 4+ years of experience in ML Engineering - data engineering, deployment and operations, MLOps and data science
  • Shown experience with the design, implementation and operation of complex ML/Data pipelines in the production environment
  • Proficiency and focus on one of the hyperscalers (AWS, Azure, GCP) in high performance, enterprise setup and with their most recent offerings in the field of ML/DS/GenAI
  • Knowledge of some MLOps tools such as KubeFlow, TensorFlow, SageMaker, ML Flow, Vertex AI, etc.
  • Strong communication and presentation skills - you´ll be a trusted partner to our clients; you will need to understand client needs, design and pitch a technical solution to the management
  • Proactive approach, analytical mindset, ability to break down complex problems; out-of-the-box thinking
  • Team leadership - ability to manage a cross-functional delivery team
  • English at a communicative level
  • EU passport - possibility of business trips

✔ Do you have experience of managing ML Engineering and/or Data science teams and projects, and a drive to get things done?

✔ Do you want to be in a client-facing role and shape the Architecture and end-to-end delivery of ML/DS projects?

✔ Are you ready for the opportunity to make a real impact of your work with various clients all over central Europe?

Join our international AI & Data team of professionals and recognized experts in the latest AI & Data technological applications to various sectors and make your skills and career reach the next level 🚀

About the team:

Do you want to build your brand by working for a leading consulting firm that drives eminence in the marketplace? Are you interested in leveraging your analytical skills and strategic ideas to improve mission execution? If so, Deloitte could be the place for you Our team brings deep industry expertise, rigorous analytical capabilities and a pragmatic mindset to help solve our client’s most complex business problems. Learn, develop, and grow in your career path

What we offer:

  • New professional challenge and leadership role - be part of the strategic growth of the AI & Data division in the Czech Republic, Central Europe and beyond
  • Diverse and complex international projects with real impact for leading companies across Europe - using the latest technologies and a holistic approach to our clients
  • Close collaboration with various experienced AI & Data teams in a casual atmosphere
  • Deloitte's dynamic environment with a stable background
  • Possibility of a hybrid working model - remote/office
  • Modern office space in the centre of Prague
  • Cafeteria with various uses: culture, travel, sports, massages, etc.
  • Long-term development and career growth at Deloitte - professional training and certification
  • And a wide range of benefits: meal vouchers, health and travel insurance, employee assistance programme, company mobile phone, laptop, BeWell 360 programme, regular team building and sports events and much more.
  • 👉 Are you interested and would you like to know more? Send us your CV and we will contact you as soon as possible.


,[International projects for global brands across industries - you will be part of an international team of AI & Data professionals based in Prague, Lead a MLOPS team and evangelize MLOPS topics within internal teams and with external clients, Client-facing role - understanding the client's business needs, designing and proposing solutions and overseeing the delivery of the solution, Engineering approach - be the link between data science, business and IT to bring solutions to life, Leading and supporting a data science delivery team - from defining success metrics, solution design, requirements gathering, data collection, data analysis, prototype implementation and testing, Work in an experienced ML engineering team - apply your expertise and develop your leadership skills while working on projects in small teams., Career and professional development through training, certifications and real-world applications] Requirements: Data engineering, MLOps, Data science, Data pipelines, AWS, Azure, GCP, Kubeflow, TensorFlow, AI

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