Machine Learning Engineer - Prototyping

Strong hands-on experience with Python for ML prototyping, data processing, and automation.
Experience building end-to-end Proof of Concepts (PoCs) and rapid prototypes.
Ability to translate ambiguous business ideas into working technical solutions quickly.
Strong data engineering skills including APIs, data pipelines, SQL, and cloud-based data handling.
Experience developing lightweight applications such as APIs, dashboards, notebooks, or simple frontends.
Good understanding of machine learning and statistical/mathematical fundamentals.
Experience working independently in fast-paced and rapidly changing environments.
Strong problem-solving, analytical thinking, and experimentation mindset.
Ability to iterate quickly based on stakeholder feedback.
Strong communication skills with the ability to clearly present findings and feasibility outcomes.
Experience delivering PoCs within short timelines (2-3 days) and scaling them into prototypes within 2-3 weeks.
Practical mindset focused on business outcomes rather than perfect production-grade code.
Experience working across the full life cycle: data ingestion - modelling - prototype delivery.