Lead - Machine Learning

Machine Learning Lead

1.

• Lead the end-to-end development of ML models for

  personalisation, ranking, recommendations, and user intent understanding

  .
• Evaluate various modelling approaches (e.g., deep learning, embeddings, hybrid recommenders) and select the best fit based on business needs.
• Drive experimentation, A/B testing, and model improvements using data-driven insights.

2. ML Infrastructure & Pipelines

• Architect and maintain

  scalable data pipelines

  for model training, retraining, and batch/real-time inference.
• Implement

  MLOps best practices

  including CI/CD for ML, feature stores, model registries, and automated monitoring.
• Ensure system reliability, low latency, and efficient resource utilisation.

3. Production Deployment & Monitoring

• Own the deployment of ML models into production, ensuring high performance and stability.
• Build robust

  monitoring systems

  to detect drift, quality degradation, and performance bottlenecks.
• Continuously improve model accuracy, relevance, and business impact.

4. Cross-Functional Collaboration

• Work closely with

  Product Managers

  to translate business goals into technical requirements.
• Partner with

  Engineering

  to integrate ML models seamlessly into user-facing features and backend services.
• Guide junior ML engineers and data scientists through mentorship and technical leadership.

Technical Expertise

• 5+ years of experience

  in Machine Learning, with strong hands-on work in

  recommendation systems

  and predictive modelling.
• Strong proficiency in

  Python

  ,

  SQL

  , and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience working with

  large-scale datasets

  , embeddings, vector search, and distributed computing (Spark, Ray, etc.).
• Solid understanding of

  MLOps practices

  Docker, Kubernetes, model registries, automated pipelines, observability tools.

Production Experience

• Proven track record of

  deploying and maintaining ML models in production environments

  .
• Familiarity with cloud platforms (AWS/GCP/Azure) and scalable data architectures.

Corporate Acumen

• Strong problem-solving mindset with the ability to balance speed and quality.
• Excellent communication skills to work with cross-functional partners.
• Ability to lead, mentor, and guide team members.