Overview: As a Mid-Level Artificial Intelligence and Machine Learning Engineer at Khonology, you will be part of a dynamic team responsible for developing cutting-edge AI and ML solutions.
You will collaborate with cross-functional teams to design, implement, and deploy AI models and algorithms to solve challenging business problems.
This role offers an opportunity to work on diverse projects and leverage the latest technologies in AI and machine learning.
Objectives Develop and deploy machine learning models.
Enhance existing Al and ML frameworks.
Implement Al-driven solutions for business challenges.
Ensure model accuracy, scalability, and performance.
Facilitate continuous improvement through model monitoring and maintenance.
Responsibilities: 1.
Model Development: Conduct exploratory data analysis to inform model development.
Develop scalable and efficient methods for large-scale data analysis and model training.
Design, develop, and train machine learning models to address specific business challenges.
Implement Al algorithms and frameworks.
2.
Model Deployment and Integration: Deploy machine learning models into production environments Integrate models with existing systems and data pipelines Ensure seamless operation of deployed models.
Collaborate with software engineers to integrate AI models into production systems.
3.
Data Preparation and Feature Engineering: Prepare and clean data for model training and evaluation.
Perform feature engineering to enhance model performance.
Implement data preprocessing and transformation pipelines.
4.
Model Evaluation and Tuning: Evaluate and benchmark the performance of AI models using appropriate metrics.
Tune hyperparameters and optimize model accuracy.
Conduct A/B testing and validation of models.
5.
Collaboration and Stakeholder Engagement: Work with data scientists, engineers, and business stakeholders to understand requirements Translate business problems into technical solutions.
Communicate findings and model performance to non-technical stakeholders.
Collaborate with team members and provide technical guidance.
6.
Research and Innovation: Research and stay up-to-date with the latest advancements in AI and machine learning technologies.
Experiment with new algorithms and techniques.
Propose innovative solutions to business problems.
7.
Documentation and Reporting: Document model development processes and methodologies.
Create user guides and technical documentation.
Report on model performance and project progress.
Requirements: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
X+ years of experience in developing AI and machine learning solutions in a professional environment.
Proficiency in programming languages such as Python, .Net or Java, or C++.
Strong understanding of machine learning techniques and algorithms, such as neural networks, SVM, decision trees, etc.
Hands-on experience with machine learning frameworks/libraries such as TensorFlow, PyTorch, scikit-learn, etc.
Experience with data preprocessing, feature engineering, and model tuning.
Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services.
Excellent problem-solving skills and ability to work independently as well as part of a team.
Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
Preferred Qualifications: PhD in Computer Science, Engineering, Mathematics, or a related field.
Experience with big data technologies such as Hadoop, Spark, etc.
Knowledge of deep learning techniques and frameworks.
Previous experience in deploying AI/ML models in production environments.
Contributions to open-source AI/ML projects or research publications.
