Senior Machine Learning Engineer (all genders) - PDR.cloud GmbH

Jobs via eFinancialCareers
United States
2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Data Analysis Microsoft Azure Software as a Service Code Review Data Cleansing Python (Programming Language) Machine Learning Rapid Prototyping Process Standard Sql Azure Machine Learning Transaction Data
+4 more
Cloud Platform System Feature Engineering IT Architecture Machine Learning Operations

Job description

  • PDR.cloud is a Berlin-based SaaS company enabling fully digital workshops for automotive repair shops - with modern IT architecture and smart solutions for complex damage processes
  • As a Senior Machine Learning Engineer at PDR.cloud, you will own the complete ML lifecycle: exploratory analysis, data modeling, feature engineering, model development, and production pipelines
  • You work hands-on across everything that comes with it - including data acquisition, schema design, data preparation, and the tools we use to evaluate our data
  • You collaborate closely with Product and Engineering using a rapid prototyping approach: validating hypotheses, iterating on models, extracting insights from data, and turning them into real product decisions
  • The role at PDR.cloud offers maximum creative freedom: you shape architecture, tooling, and data culture
  • Beyond the prototyping phase, exciting long-term challenges await: you will calibrate our models for a growing, heterogeneous customer base and continuously improve model quality, You will work primarily remote, but regularly join your team for workshops or team-building events in Berlin - for shared ideas and genuine connection beyond the screen. Flat hierarchies and short decision-making paths give you the freedom you need to work creatively, efficiently, and independently, while continuing to grow personally., * Technical interview - A technical discussion with our developers, potentially including a code review or a small practical task.
  • Team interview - An exchange with your future colleagues to ask questions and get a feel for our working environment.
  • Final conversation & offer - A joint alignment on the terms and your earliest possible start date.

We value prompt feedback and will support you throughout the entire process in an open and appreciative way.

About The Company

PDR.cloud wurde 2018 in Berlin gegründet.

Wir bieten KFZ-Reparaturdienstleistern eine cloud-basierte Software zur Abrechnung und Steuerung von Schäden.

PDR.cloud vereint die bekannten Funktionen eines klassischen Dealer-Management-Systems mit smarten Lösungen und zeitgemäßer IT-Architektur.

Unsere Mission ist es für unsere Kunden eine vollständig digitale Werkstatt zu realisieren und den Arbeitsalltag unserer Anwender trotz immer komplexer werdenden Schaden-Prozessen zu vereinfachen.

Requirements

  • Several years of experience as a Machine Learning Engineer, Data Engineer, or Applied Data Scientist with a clear engineering focus - you design pipelines yourself and solve data problems independently
  • Strong Python and SQL skills, plus confident use of a cloud platform (AWS, GCP, or Azure)
  • A solid statistical foundation beyond sklearn defaults: you know classical and probabilistic model families and understand when to apply which approach
  • Experience with production model deployment and MLOps fundamentals - you don’t need a ready-made ML platform, but build new model pipelines from scratch together with our ops professionals at PDR.cloud
  • A pragmatic, hands-on mindset: you enjoy working in rapid prototyping mode, deliver MVPs instead of over-engineered architecture, and handle incomplete data and shifting requirements with confidence

Nice-to-have

  • Experience with event or sequence data (logs, tracking events, transaction data) and irregular timestamps
  • Knowledge of probabilistic modeling or process mining
  • Experience building data and ML infrastructure in a greenfield setup
  • Background in SaaS, automotive, or insurance environments
  • Experience in agile product teams and direct collaboration with pilot customers

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