Job
- Level
- Senior
- Job Field
- Data, Application
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Berlin
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop deep learning models for real-time computer vision applications, optimizing them for deployment on resource-constrained hardware without cloud dependencies.
Job Technologies
Your role in the team
- 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.
- Arbeite eng mit Hardware-, Produkt- und Forschungskollegen zusammen, um unsere Privacy-by-Design-Architektur mitzugestalten.
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Our expectations of you
Qualifications
- 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.
- Languages: Advanced proficiency in C++ (for production-grade edge deployment) and Python (for training, research, and data analysis).
- 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.
- 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-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.
- 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.
Experience
- 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.
- AI/ML Frameworks: Extensive hands-on experience with PyTorch, and TensorFlow / Keras.
- Having work experience in a startup or venture capital is a plus.
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What we offer
- The opportunity to significantly contribute to the company's growth and success.
- A competitive salary.
- An evolving role that grows with our company's 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.
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Benefits
Health, Fitness & Fun
Topics that you deal with on the job
Job Locations
This is your employer
Peregrine Technologies GmbH
Peregrine Technologies GmbH is a Berlin-based deep-tech startup that utilizes artificial intelligence and computer vision to enhance traffic safety and urban mobility globally. The company transforms standard vehicle cameras into intelligent sensors while ensuring compliance with data protection regulations. The team comprises experts with extensive experience in robotics and machine learning.
Description
- Company Type
- Startup
- Working Model
- Hybrid, Onsite
- Industry
- Internet, IT, Telecommunication
Senior Machine Learning Engineer
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
