Engineering Director (Product)

Engineering Director (Product)
 

As an Engineering Director you will 

• Lead and manage multiple engineering teams focused on model development, evaluation, and related activities, ensuring high performance, collaboration, and delivery excellence. 

• Drive strategic planning and execution of machine learning model development and evaluation initiatives, aligning outcomes with company goals and product vision. 

• Influence and provide visibility to decision makers on modelling trends, research directions, and data-driven insights to help define strategic product priorities. 

• Coordinate cross-functionally with Research, Platform, Marketing, Leadership, and other collaborators to ensure integrated execution across model lifecycles and downstream product applications. 

• Define and implement best practices in model experimentation and evaluation methodologies to ensure scalable and reproducible results. 

• Develop comprehensive project plans, including milestones for model releases, evaluation benchmarks, resource allocations, and risk assessments. 

• Monitor project timelines, technical risks, and resource allocation across teams to maintain delivery excellence. 

• Establish, maintain, and evolve evaluation and analytics systems that measure and improve model accuracy, reliability, throughput, and fairness. 

• Report on engineering progress, research insights, and strategic needs to senior leadership; communicate technical findings clearly to both technical and non-technical stakeholders. 

• Demonstrate a data-driven and customer-centric focus in decision making, ensuring solutions are grounded in measurable outcomes and user impact. 

• Evaluate and make key technical decisions, including trade-offs between model complexity vs. efficiency, internal vs. external datasets, and experimental vs. production-ready approaches to align with company objectives. 

• Mentor engineering managers, technical leads, and other developers, fostering professional growth, technical depth, and cross-team collaboration. 

Required Qualifications 

• Master’s degree in Computer Science, Engineering, Physics, Data Science, Operations Research, or related field; or equivalent industry experience. 

• 8+ years of hands-on experience in software engineering, data science, or other relevant engineering domains, including model development or analytics. 

• 2+ years of successful leadership experience managing engineering or data-focused teams in a technology-driven environment. 

• Experience with Large Language Models and other advanced ML architectures; techniques including fine-tuning, evaluation, or benchmark design. 

• Solid understanding of modern ML development pipelines, data science practices, and model evaluation frameworks. 

• Exposure to product management, with a strong understanding of lifecycle planning and cross-functional coordination. 

• Demonstrated experience delivering high-quality analytical or model-based products on time and within scope. 

• Excellent leadership skills with the ability to motivate, guide, and develop diverse technical teams effectively. 

• Strong organizational and time-management skills, coupled with a keen eye for analytical and technical detail. 

• Exceptional communication with a perfect command of English.