Staff AI Engineer

The candidate will have responsibilities across the following functions:
Lead and Developa High-ImpactTeam:
Lead, manage and mentor a team of data scientists, fostering a culture of continuous learning and professional growth.
Guide team members in their project work and support their career development.
Will own appraisals, compensation queries, and leave management of his direct reports.
Set Strategic Vision and Drive Innovation:
Set clear goals and expectations for the team and individuals, and regularly assess and improve team performance.
Ensure alignment with organisational goals and provide technical direction.
Build Strong Cross-Functional Partnerships:
Cultivate trusted relationships with stakeholders in business, product, and engineering to identify opportunities, shape initiatives, and ensure successful implementation of data science solutions.
Act as a bridge to integrate data science seamlessly into business functions.
Implement Industry-Leading Standards for Model Quality and Monitoring:
Define robust metrics and quality standards to evaluate model performance and outcomes.
Establish and oversee best-in-class model monitoring systems to ensure reliability, scalability, and sustained impact over time.
Requirements:
Bachelor'sorMaster's degree in Computer Science, Electrical Engineering, Mathematics, Economics, or another quantitative discipline.
Demonstrates a research-oriented mindset with 6+ years of experience in data science or related fields.
Strong foundation in statistics, machine learning (e. g., Random Forests, XGBoost, SVMs), and inference techniques, with expertise in hypothesis testing, simulations, and optimisation methodologies.
Proficiency in applying deep learning algorithms to solve complex data challenges, with hands-on experience in TensorFlow or PyTorch.
Skilled in designing, executing, and scaling A/B experiments to validate and optimise data science solutions.
Advanced Python programming abilities with extensive experience in building robust data pipelines in PySpark, performing feature engineering, and optimising data workflows.
Deep familiarity with libraries and tools such as pandas, scikit-learn, SQL, and Scala, with additional experience in MLOps frameworks like Docker, Databricks, and Kubernetes for production-grade model deployment.
Demonstrated track record in developing and implementing large-scale machine learning solutions that drive business impact.
Experience in leading projects with multiple team members / managing a team is preferred.

Experience
7-11 yrs