Motopay is the fastest and most secure payment platform that connects people and grants them access to affordable products, ultimately making payments easier and more affordable than ever before.
Job Summary:
- We are seeking a Senior AI/ML Engineer with deep expertise in designing, developing, and implementing AI and machine learning solutions that drive innovation and efficiency. The ideal candidate is proficient in advanced algorithms, model optimization, and large-scale data processing. In this role, you will collaborate closely with data scientists, product managers, and software engineers to develop impactful ML solutions, contributing to the evolution of our AI powered products.
Key Responsibilities
- Model Development & Optimization: Design, build, and optimize ML models to solve complex business challenges. Regularly iterate and enhance model accuracy, performance, and scalability.
- End-to-End ML Pipelines: Develop and deploy robust ML pipelines, ensuring seamless integration with data engineering workflows and production environments.
- Data Exploration & Feature Engineering: Perform extensive data exploration and feature engineering on large, complex datasets to improve model accuracy and predictive power.
- AI Model Deployment: Lead model deployment efforts, collaborating with engineering teams to monitor and manage models in production, ensuring model performance remains high over time.
- Algorithm Innovation: Research and develop new algorithms and techniques in machine learning, deep learning, NLP, computer vision, and other AI subfields.
- Code Review & Mentorship: Conduct code reviews and provide mentorship to junior engineers, fostering a collaborative and innovative team environment.
- Stakeholder Collaboration: Work closely with cross-functional teams to align AI solutions with business needs, ensuring deliverables meet quality and performance standards.
- Documentation & Reporting: Maintain thorough documentation of ML workflows, from data preprocessing to model deployment, to ensure reproducibility and compliance with company standards
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Experience: Minimum 6 years of hands-on experience in machine learning, data science, or AI engineering, with a proven track record of deploying models in production.
- Technical Proficiency: o Strong command of Python, TensorFlow, PyTorch, and other ML frameworks. o Proficiency with data processing tools (e.g., SQL, Pandas, Spark).
- Experience with cloud platforms (AWS, GCP, or Azure) for deploying and scaling AI/ML models. o Solid understanding of MLOps practices, CI/CD for ML, and model monitoring.
- Analytical & Problem-Solving Skills: Ability to solve complex problems, analyze large datasets, and implement efficient and effective ML solutions.
- Communication Skills: Excellent verbal and written communication skills with the ability to explain complex concepts to technical and non-technical stakeholders.
- Soft Skills: Self-motivated, with strong attention to detail, and a collaborative mindset.
Method of Application
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