Senior AI Engineer in Computer Vision

Job description

As a Senior AI Engineer at Faktion you will design build and deploy computer vision systems that solve real-world problems for our customers.

The role combines hands-on machine learning with strong software engineering and MLOps practices. You will work across the full lifecycle of a machine learning system: exploring and improving datasets developing and evaluating models building training and inference pipelines deploying models to production and investigating performance issues once they are running in the field.

A significant part of the role focuses on computer vision for industrial applications including object detection image classification multispectral imagery and real-time inference. You will also contribute to the platforms and tooling that allow our engineers to train evaluate deploy and maintain machine learning models efficiently at scale.

Key responsibilities

• Develop train evaluate and maintain deep learning models for computer vision tasks such as object detection and image classification.

• Build and maintain training and inference pipelines primarily using Azure Machine Learning.

• Build data pipelines for processing large image datasets including multispectral and other multi-channel imagery.

• Explore and visualize datasets to identify data quality issues distribution shifts labeling inconsistencies and other factors that may affect model performance.

• Help define data collection annotation preprocessing feature engineering and augmentation strategies.

• Work with annotation teams to define clear labeling guidelines and ensure training data is consistent and usable.

• Train and deploy models that solve real-world problems on industrial machines and production systems.

• Optimize models for the latency throughput memory and hardware constraints of production environments.

• Debug model data and pipeline issues in production and design strategies to improve performance.

• Define appropriate validation strategies evaluation metrics and test datasets for machine learning systems.

• Perform model error analysis and translate findings into improvements in data modeling or system design.

• Prototype and evaluate new architectures algorithms and modeling approaches before integrating them into production.

• Improve our shared ML platform and tooling including internal SDKs data schemas training pipelines deployment tooling and CI/CD.

• Review pull requests and help maintain strong engineering testing documentation and code quality standards across the ML codebase.

• Collaborate with machine learning engineers software engineers data engineers and customer teams to design and deliver production-ready solutions.

• Stay up to date with relevant developments in computer vision deep learning and MLOps and assess where new approaches can provide practical value.

Job requirements

• Masters degree or PhD in Computer Science Artificial Intelligence Machine Learning or a related field or equivalent professional experience.

• Several years of professional experience building machine learning systems with a strong focus on computer vision and deep learning.

• Strong Python programming skills.

• Hands-on experience with PyTorch and/or TensorFlow.

• Solid understanding of object detection and image classification including model architectures loss functions augmentation strategies training techniques and evaluation metrics.

• Experience working with common computer vision tooling and frameworks such as OpenCV YOLO-based architectures MMDetection or similar ecosystems.

• Experience building and debugging machine learning pipelines and models in production.

• Experience with a cloud ML platform such as Azure Machine Learning AWS SageMaker or Google Vertex AI. Experience with Azure is a strong plus.

• Familiarity with Docker CI/CD automated testing versioning monitoring and other software engineering practices for production ML systems.

• Experience optimizing models for real-time or high-throughput inference ideally on edge devices or production hardware.

• Strong analytical and problem-solving skills particularly when investigating complex interactions between data models and production systems.

• Comfortable taking ownership of shared code tooling and systems used by other engineers.

• Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.

Nice to have:

• Experience building or maintaining MLOps platforms or shared ML infrastructure.

• Experience with multispectral hyperspectral or other non-standard imaging modalities.

• Experience deploying computer vision models on edge devices embedded hardware GPUs or industrial machines.

• Experience with model optimization techniques such as quantization pruning compilation or hardware-specific inference runtimes.

• Experience designing or managing large-scale image annotation and dataset curation workflows.

• Proven experience developing and deploying scalable machine learning systems.

• Experience mentoring engineers reviewing technical designs or leading technical initiatives.

• Publications or research experience in relevant AI/ML fields.

• Experience in one or more of our focus domains such as manufacturing retail data quality finance or generative AI.

We offer:

• A rewarding salary package that includes additional perks like a company car and fuel card or a mobility budget comprehensive hospitalization and group insurance along with a top-tier laptop and smartphone.

• Benefit from a company culture that stimulates both individual and team development fostering your professional growth.

• Utilize your innovation budget for engaging in exciting educational and challenging open-source projects within your guild.

• Participate in (virtual) team-building activities and gatherings a great opportunity to unwind and engage with our vibrant team initiatives.

• A flexible hybrid working-policy to choose where how and when you want to work.

Hybrid

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Senior IC

Employment Type : Full-Time
Experience: years
Vacancy: 1