Machine Learning Engineer
Budget: £10 – £15 GBP
About Us:
KYROS Insights is the only actuarial firm solely focused on loyalty programs. We help your favorite frequent flyer program, hotel, bank or retail loyalty program measure and optimize the economic value that the program creates through an innovative combination of actuarial theory, machine learning and big data technology.
We’re dedicated to delivering exceptional results to our clients. We take pride in our commitment to excellence, teamwork, and continuous improvement.
Role Overview:
For this project, you’ll be responsible for building a transformer-based deep learning model using Hugging Face libraries for a regression problem.
Key Responsibilities:
1. Algorithm Development:
* Design, develop, and implement transformer based Deep Learning models and algorithms to address specific business challenges.
* Explore and experiment with different approaches to improve model accuracy and efficiency.
2. Data Preprocessing and Feature Engineering:
* Work with large datasets, preprocess data, and engineer features to create meaningful input for machine learning models.
* Collaborate with data engineers to ensure data availability and quality.
3. Model Training and Evaluation:
* Train machine learning models using appropriate frameworks and libraries.
* Evaluate model performance using metrics relevant to the specific problem domain.
4. Deployment and Integration:
* Collaborate with software engineers to deploy machine learning models into production environments.
* Ensure seamless integration with existing systems and applications.
5. Continuous Improvement:
* Stay abreast of the latest advancements in machine learning and contribute to the continuous improvement of our models and processes.
* Participate in knowledge-sharing sessions with the team.
Qualifications:
* Proven experience as a Machine Learning Engineer, including hands-on experience in developing and deploying transformer based Deep Learning models.
* Proficiency in Pytorch, Python and PySpark.
* Expertise with Transformers and their use in NLP and Regression problems
* Strong understanding of machine learning algorithms, model evaluation, and hyperparameter tuning.
* Experience with popular machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
* Familiarity with data preprocessing, feature engineering, and model deployment.
* Excellent problem-solving skills and the ability to translate business requirements into technical solutions.
* Effective communication skills to collaborate with cross-functional teams.
KYROS Insights is the only actuarial firm solely focused on loyalty programs. We help your favorite frequent flyer program, hotel, bank or retail loyalty program measure and optimize the economic value that the program creates through an innovative combination of actuarial theory, machine learning and big data technology.
We’re dedicated to delivering exceptional results to our clients. We take pride in our commitment to excellence, teamwork, and continuous improvement.
Role Overview:
For this project, you’ll be responsible for building a transformer-based deep learning model using Hugging Face libraries for a regression problem.
Key Responsibilities:
1. Algorithm Development:
* Design, develop, and implement transformer based Deep Learning models and algorithms to address specific business challenges.
* Explore and experiment with different approaches to improve model accuracy and efficiency.
2. Data Preprocessing and Feature Engineering:
* Work with large datasets, preprocess data, and engineer features to create meaningful input for machine learning models.
* Collaborate with data engineers to ensure data availability and quality.
3. Model Training and Evaluation:
* Train machine learning models using appropriate frameworks and libraries.
* Evaluate model performance using metrics relevant to the specific problem domain.
4. Deployment and Integration:
* Collaborate with software engineers to deploy machine learning models into production environments.
* Ensure seamless integration with existing systems and applications.
5. Continuous Improvement:
* Stay abreast of the latest advancements in machine learning and contribute to the continuous improvement of our models and processes.
* Participate in knowledge-sharing sessions with the team.
Qualifications:
* Proven experience as a Machine Learning Engineer, including hands-on experience in developing and deploying transformer based Deep Learning models.
* Proficiency in Pytorch, Python and PySpark.
* Expertise with Transformers and their use in NLP and Regression problems
* Strong understanding of machine learning algorithms, model evaluation, and hyperparameter tuning.
* Experience with popular machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
* Familiarity with data preprocessing, feature engineering, and model deployment.
* Excellent problem-solving skills and the ability to translate business requirements into technical solutions.
* Effective communication skills to collaborate with cross-functional teams.