Job Description
The Role:
- Design, implement, and deploy machine learning models for predictive analytics, recommendation systems, anomaly detection, and other AI-driven applications.
- Work with large, complex datasets to perform data cleaning, feature engineering, and transformation for model training.
- Develop end-to-end ML pipelines, from data ingestion to model deployment and monitoring in production.
- Work with software engineers and product teams to integrate ML models into applications and services.
- Monitor model performance, troubleshoot issues, and implement improvements to ensure reliability and accuracy.
- Evaluate new algorithms, tools, and frameworks to enhance the company’s ML capabilities.
- Document model architectures, assumptions, and design decisions for knowledge sharing and reproducibility.
Ideal Profile:
- You possess an advanced degree, ideally a PHD, in Mathematics, Statistics, Computer Science or a related field.
- 7+ years of experience in machine learning, AI engineering, or applied data science.
- Strong expertise in Python, ML frameworks (TensorFlow, PyTorch, scikit-learn), and data processing tools (Pandas, NumPy, Spark).
- Hands-on experience designing and deploying ML models to production at scale.
- Strong understanding of supervised, unsupervised, and reinforcement learning techniques.
- Experience with cloud platforms (AWS, Azure, GCP) and deploying ML pipelines in cloud environments.
- Ability to solve complex, ambiguous technical problems and deliver production-ready solutions.
- Excellent collaboration and communication skills to work across engineering, data, and product teams.
What's on Offer?
- Great work environment
- Opportunity to make a positive impact
- Flexible working options