Senior Machine Learning Engineer

KEY ACCOUNTABILITIES:

• Architect ML systems / end-to-end pipelines / scalable and production-ready solutions

• Lead model development/pricing and ranking algorithms / improved conversion and revenue yield

• Design forecasting solutions/demand and supply models / optimized inventory and occupancy planning

• Enhance risk models/fraud detection systems / reduce cancellations and policy violations

• Establish MLOps standards/deployment and monitoring frameworks / reliable and maintainable model operations

• Drive experimentation / A/B testing and validation frameworks / data-driven product improvements

• Collaborate cross-functionally / product, engineering, and data teams / aligned metrics and business impact

• Define data strategy/feature engineering and data sourcing / improved model performance and coverage

• Ensure model governance/data quality and integrity / trusted and compliant ML systems

• Mentor team members / technical guidance and best practices / elevated team capability and output quality

• Optimize model performance/tuning and retraining strategies / sustained accuracy and efficiency

• Evaluate new approaches/algorithms and technologies / continuous innovation and competitive advantage

• Communicate insights/model performance and impact / informed stakeholder decision-making.

• Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field

• 5 8+ years of experience in applied machine learning, data science, or ML engineering roles

• Proven experience designing, deploying, and scaling ML systems in production environments

• Strong experience with large-scale data processing and distributed systems (e.g., Spark, Beam)

• Advanced proficiency in Python and ML frameworks such as TensorFlow or PyTorch

• Deep understanding of MLOps practices (CI/CD, model lifecycle management, feature stores, monitoring)

• Strong expertise in SQL and data engineering tools (Airflow, Kafka, DBT, etc.)

• Experience with experimentation frameworks and causal inference methods is a plus

• Strong system design and architecture skills for ML-driven products

• Excellent problem-solving skills with a strong analytical and business-oriented mindset

• Ability to lead initiatives, influence stakeholders, and mentor junior team members