DarkVision is seeking a Software Engineer, ML Inference to join our Imaging & AI team. You will own the software that runs our models in production: inference pipelines, performance, and the quality of the code that ships. You will help turn research-trained models into systems that run quickly and reliably on real data.You will spend most of your time on inference: preprocessing, model execution, post-processing, and making the whole path efficient on CPUs and GPUs. You will also support training and retraining infrastructure so experiments stay repeatable and models can be refreshed in a controlled way.DarkVision’s ultrasound imaging system collects huge datasets involving sub-millimetric defects across assets that span hundreds of kilometers. Reliable and automated processing of this terabyte-scale data is crucial. As a Software Engineer, ML Inference, you will focus on the design, implementation, and maintenance of the software infrastructure that allows our models to train reliably and infer efficiently.This role is on-site at our North Vancouver, BC HQ, where employees enjoy a wide array of amenities including a fully equipped gym, squash court, steam room, climbing wall, and more!Our Team Working on the Imaging & AI team, you will join a multidisciplinary group of scientists and engineers. This team is responsible for early‑stage ideation, research, experimentation, and development. You will collaborate closely with other technical members to ensure our models are integrated seamlessly into our products.What You Will DoInference Pipeline Engineering: Develop and maintain the software that moves data through preprocessing, model execution, and post-processing. Own throughput, latency, and resource efficiency (CPU/GPU utilization, I/O, batching, and parallelism).Performance Engineering: Profile inference and data paths; optimize memory use andbottlenecks; measure and improve end‑to‑end pipeline performance with clear metrics.Production Software Quality: Write clean, modular, reviewed, and tested code.



Participate in design discussions and uphold engineering standards for maintainability and reliability.Training Infrastructure and Automatic Retraining: Design and implement automated pipelines for model training and retraining. You will build systems that allow for repeatable and scalable training loops.Lifecycle Management: Establish and maintain best practices for model and dataset versioning. You will implement the tooling that tracks model lineage, connecting specific model versions to the exact data and hyperparameters used to create them.Data Integration: Write the logic required to interface with internal data ingestion systems. You will handle the efficient loading, pre‑processing, and movement of data to ensure pipelines are fed correctly.Who You Are (Basic Qualifications)Bachelor’s degree in Computer Science, Engineering, or a related field.2+ years of professional software engineering experience, including shipping and operating ML inference or deployment‑related systems.Strong proficiency in Python, with a focus on writing clean, modular, and tested code.Hands‑on experience profiling and optimizing Python for performance in data‑ or compute‑heavy workloads (e.G., profiling tools, memory/CPU hotspots, batching, parallelism).Deep practical experience with PyTorch for model execution and integration including areas such as data loading, device placement, and productive inference‑oriented usage of the framework.Demonstrated experience with model optimization and deployment for inference, such as ONNX export/conversion, TensorRT (or similar runtimes), mixed precision, and/or quantization.Understanding of high‑performance computing concepts, parallel processing,



and how inference workloads behave on GPUs and in distributed or multi‑process settings.Strong communication skills to articulate engineering trade‑offs and constraints to diverse technical teams.What Will Put You AheadComfortable reading and debugging C/C++ (e.G., native extensions, bindings, or performance‑critical libraries).Familiarity with compiler‑or graph‑based optimization paths (e.G., TorchScript, torch.Compile, Triton).Familiarity with distributed computing frameworks (e.G., Ray, Dask).Experience with MLOps tools for experiment tracking and artifact management (e.G., Weights & Biases, DVC, MLFlow).Experience with workflow orchestration tools (e.G., Prefect, Airflow, or Dagster).Working understanding of SQL and databases.General Salary Range For this role, we anticipate paying $100,000 to $150,000 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.How to Apply If you have the above qualifications, we would like to hear from you. We thank all applicants in advance, but please be advised that only those selected for an interview will be contacted.We are an equal opportunity employer. If you require accommodation or assistance at any time during the application or selection processes, please submit a request by following the directions located in the FAQ section at the bottom of the kochcareers.Com webpage.Successful candidates will be required to complete a criminal background check.Keywords: Software Engineer, ML Inference, machine learning, AI, Inference Pipeline, Systems Engineering, GPU Optimization, Performance Profiling, PyTorch, ONNX, TensorRT, Computer Vision, Industrial Imaging, Deep Learning, MLOps, Data Pipelines, Production Software, Automation.#J-18808-Ljbffr

📌 Software Engineer, Ml Inference - $100,000 - $150,000 A Year (Vancouver)
🏢 DarkVision Technologies
📍 Vancouver