• Application Deadline:
• Position: Machine Learning Engineer


• Job Type Full Time


• Qualification BA/BSc/HND


• Experience 5 years


• Location Lagos


• Job Field ICT / Computer 
  

• The Machine Learning Engineer will play a crucial role in designing, developing, and deploying state-of-the-art machine learning models and algorithms.


• S/he will collaborate with cross-functional teams to drive innovation, solve complex business challenges, and deliver scalable ML solutions.


• The ideal candidate must possess deep technical expertise in machine learning, strong programming skills, and a proven track record of delivering successful ML projects.

Responsibilities:

Research and Development:

• Conduct in-depth research on cutting-edge machine learning techniques and stay abreast of the latest advancements in the field.


• Explore and experiment with novel ML algorithms, models, and frameworks to address specific business challenges.


• Design, implement, and optimize machine learning models and algorithms to deliver robust and scalable solutions for various applications.


• Leverage data preprocessing techniques and feature engineering to enhance model performance and accuracy.

Data Management:

• Collaborate with data engineers and data scientists to ensure seamless data integration, data quality, and data pipeline efficiency.


• Work with large datasets, both structured and unstructured, to extract valuable insights and patterns.


• Develop robust testing frameworks and methodologies to evaluate the performance of ML models in real-world scenarios.


• Implement A/B testing and statistical analysis to validate the effectiveness of deployed models.

Deployment and Scaling:

• Deploy machine learning models into production environments, considering scalability and maintainability.


• Monitor model performance, conduct periodic updates, and troubleshoot issues to ensure optimal system functionality.


• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to drive ML initiatives and achieve project goals.


• Provide technical leadership and mentorship to junior members of the ML engineering team.

Documentation and Communication:

• Document all development processes, methodologies, and experimental results to facilitate knowledge sharing and future enhancements.


• Communicate complex technical concepts and findings to both technical and non-technical stakeholders effectively.


• Perform other duties as assigned.

Requirement:

• Bachelor’s or master's in computer science, Data Science, Machine Learning, or a related field.


• 5+ years of industry experience as a Machine Learning Engineer, developing and deploying ML models in real-world applications.


• Expert knowledge with a scripting language (e.g. Python) and with an object-oriented language (e.g. C++, Java).


• Strong understanding of machine learning algorithms, statistical modeling, and optimization techniques.


• Proficiency in the development, validation, implementation, and production launch of machine-learning algorithms and models.


• A passion for implementing coding best practices across a team.


• Strong leadership skills. Must be able to define and direct the scope of work of Junior team members.


• Experience with popular ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).


• Solid knowledge of data processing, feature extraction, and data visualization techniques.


• Ability to create logical data models by combining data from multiple sources including internal, and external data.


• Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation.


• Familiarity with cloud computing platforms and distributed systems for scalable ML deployments.


• Excellent problem-solving, analytical, and communication skills.


• Ability to work collaboratively in a fast-paced and dynamic environment.


• Deep appreciation for diversity of thought and a proponent for collaborative solutions.


• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences.