Senior Machine Learning Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Create, implement, and enhance machine learning and computer vision models to improve product features.

• Investigate, assess, and utilize CNNs, transformers, and vision-language models.

• Execute and evaluate algorithms on extensive datasets to measure accuracy and throughput.

• Refine large-scale models utilizing LoRA and QLoRA techniques.

• Establish, apply, and track evaluation metrics such as precision, recall, ROC-AUC, and confusion matrices.

• Examine training, testing, and production data to pinpoint performance shortcomings and reliability threats.

• Enhance model accuracy, robustness, and system reliability through data-driven improvements.

• Assist in the complete machine learning workflow, encompassing data preparation, training, deployment, monitoring, and iteration.

• Contribute to CI/CD pipelines and production monitoring to ensure dependable, reproducible, and scalable model delivery.

• Identify and address model performance regressions and production challenges.

• Guide junior CVML engineers throughout various phases of machine learning projects.

• Engage in design reviews, technical discussions, knowledge sharing, and Agile ceremonies.

• Propose enhancements to models, workflows, tools, and product functionalities.

• Collaborate with engineering, product, and data teams.

• Keep abreast of new ML and computer vision trends and evaluate their practical applications.

⛳️ Requirements

• Bachelor’s degree or higher in Computer Science, Electrical Engineering, or a related discipline, or equivalent experience.

• Extensive hands-on experience in developing and deploying machine learning models in production settings.

• Advanced knowledge in supervised, unsupervised, and semi-supervised learning methodologies.

• Proficient in classification, regression, clustering, and anomaly detection techniques.

• Familiarity with convolutional neural networks, recurrent neural networks, and transformer-based models.

• Strong skills in Python and PyTorch programming languages.

• Experience with object detection, image segmentation, and representation learning techniques.

• Knowledge of computer vision and scientific computing libraries like OpenCV.

• Understanding of model deployment, monitoring, and CI/CD workflows.

• Experience with large-scale datasets and performance-sensitive machine learning systems is advantageous.

• Previous experience mentoring or providing technical guidance to ML engineers is preferred.

• Familiarity with production MLOps practices and model lifecycle management is a plus.

• Capable of balancing research-oriented exploration with practical, production-focused execution.

🏝️ Benefits

• Equal opportunity employer dedicated to fostering a diverse and inclusive workplace.

• Reasonable accommodations available throughout the interview process.

• Comprehensive benefits information provided by the Talent Attraction team.