Lead/Staff Machine Learning Engineer

Stellenbeschreibung:

At CloudFactory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world. By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale. 

More than just a workplace, we're a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following.

Our Culture

At CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are:

  • Mission-Driven: We focus on creating economic and social impact.
  • People-Centric: We care deeply about our team's growth, well-being, and sense of belonging.
  • Innovative: We embrace change and find better ways to do things together.
  • Globally Connected: We foster collaboration between diverse cultures and perspectives.

If you're passionate about innovation, collaboration, and making a real impact, we'd love to have you on board

Role Summary

We are seeking a highly-skilled and experienced ML Engineer to join our team with demonstrable experience in prototyping, building, and deploying end-to-end computer vision solutions.

As a valued member of the team at CloudFactory, you will play a crucial role in developing and implementing cutting-edge software solutions that enhance our machine learning and core business capabilities. You will work closely with cross-functional teams to design and build vision AI products and solutions to support automation of annotation, label QA, model training, and more.

If you are enthusiastic about the opportunity to make a difference in the world while working alongside talented individuals from developing nations, then CloudFactory is the perfect fit for you.
Responsibilities:

In our team, you will be building models that help humans annotate faster with as little data as possible. You will also work on simplifying the complexities of vision AI for users, so you need very good in-depth knowledge of most computer vision AI techniques. You would collaborate closely with ML engineers and be able to communicate complex issues clearly to stakeholders from the tech, product, or business teams.

Requirements

  • Degree in applied mathematics, statistics, computer science, physics, engineering, a quantitative or computation field. MS or PhD preferred
  • 3+ years applying machine learning to practical uses
  • Experience working in computer vision
  • Fluent in Python and writing production ready code
  • Experience with deep learning frameworks such as PyTorch and TensorFlow
  • Knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks
  • End-to-end experience bringing ML models to production or building ML pipelines
  • Knowledge of LLMs or generative AI systems, including prompt engineering, fine-tuning, or retrieval-augmented generation (RAG)

Extras that would be great to have

  • Experience with model optimization techniques
  • Experience using Golang
  • Comfortable with SQL databases
  • Knowledgeable about docker/kubernetes

Benefits

At CloudFactory, we believe that work should be more than just a job—it should be a platform for growth, impact, and community. Here, you'll earn with purpose, learn every day, and serve a mission that truly matters. If you're looking for a career where you can develop professionally, contribute meaningfully, and be part of a global movement, we'd love to have you on this journey

Join us today and be part of our mission to connect people and technology for a better world Apply now and bring your whole, authentic self to work—we can't wait to meet you

NOTE / HINWEIS:
EnglishEN: Please refer to Fuchsjobs for the source of your application
DeutschDE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung

Stelleninformationen

  • Veröffentlichungsdatum:

    25 Jan 2026
  • Standort:

    Berlin
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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