Machine Learning Engineer

We are looking for a Machine Learning Engineer to develop, evaluate, and improve machine-learning models and pipelines for our products. You will work closely with Tech Leads, Data Engineers, Backend Engineers, and DevOps to turn approved use cases into reliable and reproducible ML solutions.
Key Responsibilities

• Translate use cases into modelling tasks, experiments, baselines, and evaluation metrics.
• Prepare datasets, features, and reproducible training/evaluation pipelines.
• Train, fine-tune, compare, and optimise ML models.
• Analyse model performance, errors, robustness, bias, latency, and cost.
• Track experiments, model versions, and data lineage.
• Define inference requirements and collaborate on deployment and monitoring.
• Document model limitations, failure modes, and evaluation results.

Requirements

• Strong Python and machine-learning fundamentals.
• Hands-on experience with model training, evaluation, and optimisation.
• Experience with data preparation, feature engineering, and experiment design.
• Familiarity with ML frameworks such as PyTorch or TensorFlow.
• Understanding of model deployment, monitoring, and reproducible ML workflows.
• Strong analytical and problem-solving skills.
• Ability to communicate technical findings clearly and work effectively in cross-functional teams.

Nice to have: Experience with LLMs / Generative AI, MLOps, Docker, cloud infrastructure, or model serving.