Your key responsibilities (18+ years Only)

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 practicesCI/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.

Director of Artificial Intelligence (AI Tech Lead)(18+ years Only)