Machine Learning Engineer

We are seeking a highly skilled and motivated Machine Learning Engineer to join our team and contribute to the development of cutting-edge solutions for child safety applications. As a Machine Learning Engineer, you will be responsible for:
● Training and enhancing machine learning models using image-based data on TensorFlow.
● Evaluating and enhancing the performance of existing ML models, identifying opportunities for targeted advancements.
● Advising and guiding on the full ML development lifecycle, from conception to deployment, ensuring robust, efficient, and scalable solutions.
● Developing strategies for continual model training and retraining to adapt to evolving data patterns and threats, including training models in remote and sensitive environments.
● Innovating and exploring new ML development pathways, including the integration of open-source multi-modal models for advanced image and video classification tasks.
● Customising and fine-tuning state-of-the-art ML models to align with company-specific use cases and client needs.
● Architecting and implementing solutions for on-device model deployment, emphasising user privacy and data security.
● Creating and maintaining model deployment packages, such as SDKs and Docker containers, for seamless client integration.
● Collaborating cross-functionally with product managers, software engineers, and other stakeholders to integrate ML solutions into our product suite.
● Staying abreast of the latest ML technologies and methodologies, advocating for the adoption of industry-best practices.
Qualifications:
● Bachelor's or Master's degree in Computer Science, Engineering, or related field.
● Proven experience in machine learning model development and deployment,
particularly with TensorFlow.
● Strong programming skills in Python and proficiency in ML libraries such as
TensorFlow, PyTorch, or Keras.
● Experience with image-based data and advanced image processing techniques.
● Knowledge of model evaluation metrics, optimization algorithms, and deep learning
architectures.
● Familiarity with cloud platforms for model deployment (e.g., AWS, Google Cloud).
● Ability to work independently and collaboratively in a fast-paced environment.
● Excellent communication skills and the ability to explain complex concepts to
non-technical stakeholders.
Bonus Skills:
● Experience with on-device model deployment and edge computing.
● Familiarity with privacy-preserving ML techniques and data security protocols.
● Knowledge of open-source ML models and their integration into custom applications.
If you are passionate about leveraging machine learning for child safety applications and are excited to work on impactful projects, we encourage you to apply and be part of our innovative team!