Job Description We are seeking a talented and experienced Machine Learning Engineer specializing in image-based networks to join our dynamic team. As a Machine Learning Engineer, you will play a pivotal role in developing and deploying state-of-the-art models and algorithms for tasks such as image generation, recommender engines, prediction models, and more. Your work will directly contribute to advancing our cutting-edge machine learning capabilities. Responsibilities:
Analyse and preprocess large-scale datasets for training and evaluation purposes.
Experiment with different architectures, loss functions, and data augmentation techniques to improve model performance.
Collaborate with cross-functional teams to define project requirements and deliver innovative solutions.
Stay up-to-date with the latest advancements in machine learning and computer vision, and apply them to solve complex problems.
Troubleshoot and debug issues related to model training, performance, and scalability.
Integrate the training software into our continuous integration cluster to support metrics persistence across experiments, weekly/nightly neural network builds, and other unit / throughput tests.
Collaborate with software engineers to integrate machine learning models into production systems.
Document research findings, experiments, and algorithms in technical reports and presentations.
Qualifications
Proven industry experience (2+ years) in developing and deploying deep learning machine learning models.
Solid understanding of deep learning concepts, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and/or graph neural networks (GNNs).
Strong programming skills in Python, including proficiency in one or more deep learning frameworks (Tensor Flow, Py Torch, Keras). Py Torch preferred.
Experience with image processing techniques, computer vision libraries (Open CV), and related tools.
Familiarity with AWS infrastructure and toolchain (Sage Maker, Cloud Formation, Cloud Watch, etc.)
Ability to preprocess and manipulate large datasets using tools such as Num Py, Pandas, and scikit-learn.
Knowledge of software engineering principles, including version control (Git) and agile development methodologies.
Excellent problem-solving skills, with the ability to work on complex machine learning challenges independently.
Strong written and verbal communication skills, with the ability to effectively collaborate with team members and present findings to stakeholders.
We offer:
Flexible working format - remote, office-based or flexible
A competitive salary and good compensation package
Personalized career growth
Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
Active tech communities with regular knowledge sharing