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Machine Learning Engineer
2 months ago
- Collaborate with cross-functional teams to define and prioritise machine learning projects.
- Design, implement, and optimise machine learning models, with a strong focus on building robust and scalable training pipelines.
- Develop data preprocessing workflows, feature engineering methods, and model training processes.
- Implement automation in model training, validation, and deployment processes to enhance efficiency.
- Conduct experiments to evaluate model performance and iterate based on findings.
- Stay current with the latest advancements in machine learning, particularly in areas related to training optimisation and efficiency.
- Mentor and guide junior engineers, promoting a culture of continuous learning and technical excellence.
- Contribute to the strategic planning and growth of the company by providing technical insights and recommendations.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related field.
- Proven experience in developing and deploying machine learning models with a focus on training pipeline design and optimisation.
- Strong programming skills in Python and proficiency with machine learning libraries such as TensorFlow, PyTorch, or similar.
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Proficiency in designing and managing data pipelines and training workflows.
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerisation technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to work independently in a fast-paced startup environment.
- Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.
- Ph.D. in a relevant field or equivalent industry experience.
- Experience with large-scale model training, distributed computing, or model optimisation techniques.
- Prior experience working in a startup or early-stage company.
- Contributions to open-source machine learning projects or publications in top-tier conferences.
- Competitive salary and equity compensation.
- Opportunity to work on cutting-edge AI technologies and make a meaningful impact.
- Collaborative and inclusive company culture.
- Professional growth and development opportunities.