ML/MLOps Engineer

We are looking for an ML Engineer with 3+ years of commercial experience to develop, deploy, and support production-ready machine learning solutions.

Responsibilities
Develop, train, and evaluate ML models.
Build and maintain end-to-end ML pipelines.
Prepare data and perform feature engineering.
Deploy models and integrate them with backend services.
Monitor model performance and optimise production solutions.

Requirements
3+ years of commercial experience in Machine Learning or ML Engineering.
Strong Python skills.
Experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tools.
Experience with pandas, NumPy, SQL, APIs, Docker, and Git.
Experience with AWS, Azure, or GCP.
Understanding of the full ML lifecycle, including training, validation, deployment, and monitoring.
English sufficient for technical communication.

Nice to Have
Knowledge of MLflow, SageMaker, Azure ML, Vertex AI, or similar platforms.
Experience with Kubernetes, CI/CD, Terraform, or PySpark.
Experience in Computer Vision, NLP, recommendation systems, anomaly detection, or time-series modelling.

What We Offer
Fully remote work.
Hands-on projects with international clients.
Career growth and senior mentorship.
Modern tools and collaborative teamwork.