Senior Machine Learning Engineer
hace 20 horas
Bristol
What you will do as a Senior ML Engineer • Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics., • Own the ML lifecycle from data preparation through training, evaluation, and deployment., • Implement and maintain MLOps workflows for continuous integration and delivery of ML models., • Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability., • Contribute to architecture decisions for ML pipelines and data flows., • Apply secure coding and configuration practices in line with compliance standards., • Mentor junior engineers and share best practices across the team., • Support innovation by researching emerging ML techniques and tools. What you’ll bring • Proven experience developing and deploying machine learning models in production environments., • Proven experience with the OpenCV framework and various object detection models, including YOLO, RCNN, and Vision models, along with a clear understanding of when to apply each model., • Proficiency with object detection concepts. Experience in video analysis, particularly optical flow and object tracking., • Solid knowledge of Optical Character Recognition (OCR) models, with the ability to fine-tune these models using custom datasets., • An understanding of how to measure the accuracy of text extractions through metrics like Character Error Rate (CER) and Word Error Rate (WER) is also crucial., • Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch)., • Understanding of ML architectures, hyperparameter tuning, and performance optimisation., • Experience with MLOps tools and CI/CD pipelines., • Familiarity with data engineering concepts (ETL, data pipelines, SQL)., • Ability to analyse complex data and communicate insights effectively., • Strong problem-solving skills and attention to detail., • Excellent collaboration and stakeholder engagement skills. Core areas (must have): • ML Development Expertise: Hands-on experience building and deploying ML models., • Lifecycle Ownership: Ability to manage ML workflows from design to production., • Tool Proficiency: Skilled in Python, ML frameworks, and MLOps tooling., • Data Engineering Awareness: Understanding of data pipelines, warehousing, and integration., • Governance & Compliance: Familiarity with secure coding and quality assurance standards., • Collaboration & Mentoring: Ability to work across teams and support junior engineers., • Continuous Improvement: Commitment to learning and applying emerging ML techniques., • Desirable:, • Experience with cloud platforms (AWS) and containerisation (such as Docker, Podman, Kubernetes)., • Exposure to big data technologies (Spark, Hadoop) and Apache tools., • Knowledge of NLP, computer vision, and deep learning architectures., • Familiarity with Agile and DevOps practices., • STEM degree or equivalent experience in AI, Data Science, or related fields., • Industry certifications (e.g., TensorFlow Developer, AWS Machine Learning Specialty)., • Experience working in secure or regulated environments. SC clearance is manadaorty for this role