Senior Machine Learning Engineer

Ensign is hiring !

Strategic Leadership & Team Management

• Define and own the ML roadmap for Reasoning Analytics, aligning team priorities with business objectives and long-term product vision.
• Lead a team of ML engineers and data scientists; conduct code reviews, set development standards, and foster a culture of technical excellence.
• Establish best practices for experimentation, model governance, and documentation across the ML engineering function.
• Manage capacity planning, sprint rituals, and delivery timelines; escalate risks proactively.
   

Model Development & Optimisation

• Architect and oversee the design, development, and optimisation of production-grade ML models using frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
• Collaborate with domain experts and data engineers to define feature strategies, validate data quality, and build robust training pipelines.
• Guide the team on algorithm selection, hyperparameter tuning, model evaluation, and validation to ensure high accuracy, performance, and scalability.
• Identify and resolve model performance bottlenecks, optimising for latency, throughput, accuracy, and resource utilisation.
   

MLOps & Production Deployment

• Maintain CI/CD pipelines for model training, validation, and deployment to production environments.
• Partner with DevOps and platform engineering teams to integrate models into applications, services, and edge infrastructure.
• Establish monitoring, alerting, and automated retraining workflows to ensure deployed models remain performant, reliable, and drift-free.
   

Research, Innovation & Continuous Improvement

Stay at the forefront of ML/AI research; evaluate emerging algorithms, tools, and frameworks for applicability to the team’s problem domain.
Ensure a culture of experimentation— deliver quick proof-of-concept initiatives.
Contribute to the broader ML community through publications, open-source contributions, or conference participation where appropriate.