Machine Learning Scientist

4 weeks ago

Vancouver, Canada DarkVision Full time

**Your Job**
DarkVision, part of Koch Engineered Solutions, is looking for a Machine Learning Scientist for a temporary position with a 1-year term. DarkVision's ultrasound imaging asset inspection system collects huge datasets in the order of hundreds of gigabytes that are several kilometers long where a defect may be on the order of a few millimetres. It is essential that we develop algorithms for automated processing, measuring, classification, and visualization of this data since manual processing is both time consuming and inconsistent.

As a Machine Learning Scientist, you will be involved in researching, designing, and implementing deep learning architectures that learn efficient generalizable representations for several vision-based tasks. You will report to our Vice President of Research & Innovation and be responsible for developing machine learning pipelines for continuous training, evaluation, and deployment of deep learning models.

Our management process is light and generally milestone driven, using pseudo-Agile sprints derived from our quarterly and yearly goals. All goals are internally generated with plenty of room for feedback.

This is a temporary position with a 1-year term. It is on-site in our HQ in North Vancouver, BC.

**Our Team**

With the largest ultrasound datasets globally, DarkVision's Research & Innovation team unites top-tier PhDs, engineers, and research scientists to pioneer automated image processing and deep learning architectures.

**What You Will Do**
- **Research**: Rapid model prototyping, training, and deployment of state-of-the-art deep learning models to solve large-scale industrial problems. You will be investigating image classification, object detection, instance segmentation, semantic segmentation, anomaly detection, and other bespoke tasks for processing industrial ultrasonic array data.
- **Pipeline**: Work with our ML Ops team to build cloud-based pipelines for large-scale image pre-processing, data-augmentation, training, post-processing, and inference.
- **Deploy**: Work with the Software Development Team to deploy model in production for its end-users.
- **Monitor**: Continuously monitor success matrices of the assigned ML project and make continuous improvements for increasing model robustness and efficiency.
- **Data Analysis**: Work closely with our Data Analysts to explore, analyze, and organize data; perform data extraction and preprocessing for training and evaluation purposes.
- **Document**:Document model architecture, training details, dataset extraction, and cleaning procedures for reproducibility, product management, and internal training.

**Opportunities to Learn**
- Exploration of the state-of-the-art methodologies in computer vision like self-supervised learning and unsupervised learning for the purpose of non-destructive testing.
- Exposure to full ML lifecycle and orchestration management tools like Prefect, Kubeflow, AWS SageMaker, Weights, and Biases.
- Converting ideas into intellectual property assets (e.g. patents).

**Who You Are (Basic Qualifications)**
- Experience developing and training deep learning models from scratch.
- Master's degree in Computer Science, Computer Engineering, Electrical Engineering or a ML/AI related field; PhD preferred.
- Proficient in Python and at least one mainstream deep learning framework, such as PyTorch, TensorFlow, JAX, etc.

**What Will Put You Ahead**
- Experience with medical or industrial ultrasound images for deep learning-related projects.
- Experience in deep learning projects for industrial non-destructive testing.
- Experience leading and mentoring ML engineers and ML scientists.
- Hands-on experience with ML lifecycle management tools like MLFlow, Amazon SageMaker, GPC Vertex AI, etc.
- Hands-on experience with orchestration tools like Kubeflow, Prefect, Airflow, etc.
- Working knowledge of Git, Docker, and cloud services like AWS and GPC.
- Publications in top tier venues likes CVPR, ICCV, etc.
- Experience with Reinforcement Learning and/or Few-shot Learning
- Experience with NLP (Transformers, RNNs)
- Experience in self-supervised and/or unsupervised learning
- Experience with Generative Model / Diffusion
- Experience with Causal Inference
- Great communicator with excellent data presentation, and report writing skills.
- Be able to work in a fast-paced, self-driven environment.

**General Salary Range**

For this role, we anticipate paying $100,000 - $180,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

**Who We Are**

DarkVision Technologies Inc. is a Canada-based tech company disrupting the industrial imaging market since 2013. We have created the world's most advanced acoustic-based imaging platform. We are packaging it into multiple new product lines, revolutionizing how our clients quantify and visualize the integrity of their critical assets.

Backed by Koch Industries, one of the world's largest privately held companies, Da

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