Your key responsibilities
- Proven ability to design, build, and deploy end-to-end AI / ML systems in production.
- Expertise in data science , including statistical analysis, experimentation, and data storytelling.
- Experienced in working with large-scale, real-world datasets for model training and analysis.
- Comfortable navigating urgency, ambiguity, and fast-changing priorities . Skilled at solving complex ML problems independently , from idea to implementation.
- Strong leadership experience building and guiding high-performing AI teams . Hands-on with deep learning, NLP, LLMs , and classical ML techniques. Fluent in model experimentation, tuning, optimisation , and evaluation at scale.
- Solid software engineering background and comfort working with data and full-stack teams .
- Experience with cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines.
- Bias for action — willing to jump into code, data, or ops to ship impactful AI products .
Your skills and experience
PhD in Computer Science, Data Science, Machine Learning, AI, or a related field.Strong programming skills in Python (preferred), with experience in Java, Scala, or Go a plus.Deep expertise with ML frameworks like TensorFlow, PyTorch, Scikit-learn.Experience with large-scale datasets , distributed data processing (e.g. Spark, Beam, Airflow).Solid foundation in data science : statistical modelling, A / B testing, time series, and experimentation.Proficient in NLP, deep learning , and working with transformer-based LLMs .Experience with MLOps practices —CI / CD, model serving, monitoring, and lifecycle management.Hands-on with cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks.Strong grasp of API design , system integration, and delivering AI features in full-stack products.Comfortable working with SQL / NoSQL and data warehouses like BigQuery or Snowflake.Familiar with ethical AI, model explainability , and secure, privacy-aware AI development.