Senior Machine Learning Engineer (mf)


Job Location:

Berlin - Germany

Monthly Salary: Not Disclosed
Posted on: 11 hours ago
Vacancies: 1 Vacancy

Job Summary

About Peregrine

Based in Berlin were leveraging the power of AI to transform cameras into intelligent devices enhancing road safety and urban mobility on a global scale while preserving privacy at all times.

At Peregrine diversity and international collaboration fuel innovation. We unite the brightest minds with strong academic backgrounds and rich industry experience in robotics and machine learning spanning from the tech hubs of Silicon Valley to the engineering powerhouses of Europe. Our team boasts alumni from leading automotive giants like Bosch Volkswagen IAV and TomTom and institutions such as the ETH in Zurich. Were on the hunt for brilliant dynamic and passionate individuals eager to tackle challenging problems and make a tangible impact.

Tasks

The Role

As a Senior Machine Learning Engineer you will own the design training and on-device deployment of the computer vision models at the heart of our product. You will work at the intersection of research and production turning state-of-the-art vision techniques into reliable systems that run within strict latency and privacy constraints on resource-constrained edge hardware. Your key tasks will include:

  • Design train and optimize deep learning models for object detection semantic segmentation pose estimation and tracking.
  • Port and deploy models to resource-constrained edge hardware achieving single-digit millisecond latency without cloud dependencies.
  • Build and maintain robust vision pipelines from data ingestion through training to production inference.
  • Apply model compression techniques such as quantization pruning knowledge distillation and neural architecture search to meet strict performance budgets.
  • Develop synthetic data and domain adaptation pipelines to close the sim-to-real gap.
  • Profile inference pipelines end-to-end to identify and eliminate bottlenecks on target silicon.
  • Translate cutting-edge academic research into highly reliable production-grade systems.
  • Collaborate closely with hardware product and research colleagues to shape our privacy-by-design architecture.

Requirements

Your Profile

Core Competencies: Computer Vision & Edge AI

  • Edge AI & On-Device Inference: Expertise in porting deploying and optimizing complex deep learning models for local resource-constrained hardware without cloud dependencies.
  • Advanced Computer Vision: Deep knowledge of developing vision pipelines for object detection semantic segmentation pose estimation and tracking.
  • Hardware-Aware Architecture Design: Ability to custom-build network topologies tailored to specific sensors and strict latency budgets rather than relying on off-the-shelf APIs.
  • Synthetic Data & Domain Adaptation: Proven experience in building simulation pipelines for synthetic data generation and closing the sim-to-real gap using Domain Randomization and GANs.

Technical Stack & Tools

  • Languages: Advanced proficiency in C (for production-grade edge deployment) and Python (for training research and data analysis).
  • AI/ML Frameworks: Extensive hands-on experience with PyTorch and TensorFlow / Keras.
  • Optimization & Deployment: Mastery of inference acceleration and model conversion using TensorRT ONNX and OpenVINO.
  • Model Compression: Practical application of quantization pruning knowledge distillation and neural architecture search.

System Architecture & Compliance

  • Privacy-by-Design Architecture: Designing robust local AI systems that guarantee data sovereignty and strict GDPR compliance without cloud roundtrips.
  • Performance Profiling: Deep-dive auditing of inference pipelines to identify bottlenecks and achieve single-digit millisecond latency on target silicon.

Research Strategy & Leadership

  • Research-to-Production (R2P): The ability to translate complex state-of-the-art academic research into highly reliable systems that work in the real world.
  • AI Strategy & Assessment: Capability to conduct feasibility studies ROI analysis and privacy-first architecture blueprinting.

Mindset

  • Comfort with ambiguity a problem-solving mindset and adaptability to rapid change.
  • Entrepreneurial drive a strong sense of responsibility high ambition and a collaborative approach to achieving goals.
  • Excellent verbal and written communication skills in English and the ability to effectively collaborate with various stakeholders.
  • Having work experience in a startup or venture capital is a plus.

We dont expect anyone to check all these boxes mentioned above! If a few of these points apply to you we want to talk!

Benefits

Our offering

  • The opportunity to significantly contribute to the companys growth and success.
  • A competitive salary.
  • An evolving role that grows with our companys journey.
  • We have flexible working hours and a need-based work-from-home policy; all processes are being set up for remote first.
  • A diverse and inclusive work environment as well as a flat organizational structure fast decision making within the team disagree & commit.
  • We foster a culture where we all learn from each other and value new ideas.
  • We hold fun team events throughout the year.
  • We contribute to your monthly public transport ticket.
  • Free drinks snacks and coffee.
About PeregrineBased in Berlin were leveraging the power of AI to transform cameras into intelligent devices enhancing road safety and urban mobility on a global scale while preserving privacy at all times.At Peregrine diversity and international collaboration fuel innovation. We unite the brightest...

About Company

At Peregrine Technologies we empower companies to build a safer and more sustainable mobility ecosystem for all using video analytics.

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