The ML Engineer will be responsible for designing, building, and deploying machine learning models to solve complex business problems. This role involves creating a scalable and efficient environment for data scientists to develop and experiment with models. The ML Engineer will work closely with data scientists to understand their needs, optimize model performance, and ensure seamless integration with existing systems. The ideal candidate will have a strong background in machine learning, software engineering, and cloud-based infrastructure, with a focus on scalability, performance, and reliability. This position requires excellent problem-solving skills, a collaborative mindset, and the ability to stay updated with the latest advancements in machine learning technologies. Key Responsibilities:
- Create, train, and deploy machine learning models to address complex business challenges.
- Develop and maintain scalable, efficient, and robust environments for data scientists to experiment and develop models.
- Work closely with data scientists to understand their requirements, provide technical support, and optimize model performance.
- Ensure seamless integration of machine learning models with existing systems and workflows. Optimize Model Performance: Continuously monitor and improve the performance, accuracy, and efficiency of machine learning models.
- Apply best practices in software engineering, including version control, testing, and documentation, to machine learning projects.
- Keep abreast of the latest advancements in machine learning technologies and methodologies, and apply them to improve existing solutions.
- Implement and maintain data security and privacy measures in all machine learning projects.
- Develop and maintain automated pipelines for data preprocessing, model training, and deployment.
- Provide guidance and training to junior team members and data scientists on machine learning best practices and tools.
Qualifications:
- 3+ years experience in data engineering or machine learning functions
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Proven experience in designing, building, and deploying machine learning models in a production environment.
- Proficiency in Python.
- Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
- Knowledge of software engineering best practices, including version control (e.g., Git), testing, and documentation.
- Strong analytical and problem-solving abilities to tackle complex business challenges using machine learning.
- Excellent communication and teamwork skills to work effectively with data scientists, engineers, and other stakeholders.
- Experience in developing and maintaining automated pipelines for data preprocessing, model training, and deployment.
