Machine Learning Engineer

Job Summary

This role leads the strategic development and execution of machine learning initiatives within the organization. As a supervisor Machine Learning Engineers, the role involves setting the technical direction, overseeing project delivery, and ensuring the team’s alignment with business objectives. Machine Learning Specialist will also collaborate with cross-functional teams to ensure that ML solutions are efficient, scalable, and impactful.

Duties and Responsibility

• Define the strategy and roadmap for machine learning initiatives across the organization.
• Provide technical guidance, performance reviews, and mentorship to team members.
• Oversee the design, development, and deployment of ML models that solve complex business problems.
• Ensure that ML models are scalable, secure, and comply with data privacy and governance regulations as well as project budgets, timelines, and resources.
• Lead research efforts to explore new technologies and methodologies in machine learning to maintain a competitive edge in technologies and practices.
• Monitor model performance, ensure continuous improvement through optimization, and address production issues as needed.
• Enforce SSHE policies and environmental compliance in all working areas.
• Perform other related duties as assigned

Key Measurement

• Successful rate of model deployment (accuracy, precision, recall, etc.).
• ML projects deliverables.
• Percentage improvement in model performance and optimization.
• ML initiative impacts on business goals.
• Innovation in machine learning methods.

Experience

• Bachelor Degree of Machine Learning, AI, Data Science, Computer Science or related field.
• 5-7 years of experience machine learning, AI, and data science, with a proven track record of leading teams and delivering impactful ML projects.
• Hands-on experience in developing and deploying machine learning models in production environments.
• In-depth experience with data preprocessing, feature engineering, model training, and optimization.
• Experience in deploying ML systems at scale and ensuring high availability and performance

Skills and Abilities

• Expertise in machine learning algorithms, frameworks, and tools.
• Advanced knowledge of programming languages.
• Strong understanding of cloud platforms for ML and distributed computing frameworks.
• Knowledge of deep learning, reinforcement learning, and natural language processing.
• Strong leadership and decision-making skills, with experience in managing and developing teams.
• Strategic thinking and the ability to guide long-term technology planning.
• Ability to translate complex technical concepts into business-focused solutions.
• Strong analytical and problem-solving skills.
• Good interaction skills stakeholders and cross-functional teams management.
• Excellent communication for explaining technical concepts to non-technical stakeholders and collaborating with diverse teams.

Competencies