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Machine Learning Engineer - Python/R (3-8 yrs)

3-8 years

Machine Learning Engineer - Python/R (3-8 yrs)

Zallery

posted 4d ago

Job Description

Job Description :


We are seeking an experienced Machine Learning Engineer to join our dynamic and innovative team. As a Machine Learning Engineer, you will play a key role in developing and implementing machine learning models to solve complex business problems. You will collaborate with cross-functional teams to understand requirements as well as deliver scalable and efficient ML solutions.

Responsibilities :

- Developed and implemented advanced machine learning models to address specific business challenges


- Explore the data and identify differences in data distribution that could impact performance when deployed


- Train, evaluate, and fine-tune machine learning models using appropriate frameworks and tools


- Work with data scientists to implement data preprocessing and feature engineering infrastructure to improve model performance


- Optimize machine learning models for scalability and efficiency, considering real-time and batch processing requirements


- Ensure code quality, maintainability, and documentation standards are met. Write clear and concise technical documentation


- Stay updated on the latest advancements in machine learning and contribute to the research and innovation within the field


- Propose and implement improvements in existing model development


- Work closely with data scientists to define collection events and data transformations needed to drive personalized learning


- Work closely with Product Owners to understand potentials and limitations of AI models developed and deployed


- Provide guidance and mentorship to junior members of the team


- Adhere to ethical standards and comply with data laws and regulations applicable to the job function


- Clearly communicate findings to senior leadership


Required Skills :


- Experience with Python-based AI/ML frameworks, Java, and/or R


- Experience with ML frameworks (like Keras, PyTorch, Tensorflow) and libraries (like scikit-learn)


- Experience working with large datasets, handling data preprocessing tasks, and exploring data to identify patterns and insights


- Knowledge and practical application of statistical analysis and mathematical modeling concepts and principles


- Proficiency in cloud services like SageMaker, S3, EC2, Azure Machine Learning


- Ability to containerize machine learning applications for portability and reproducibility


- Understanding of container orchestration for managing and scaling containers in a cloud environment


- Knowledge of serverless computing for executing code without managing the underlying infrastructure


- Experience with object storage for managing large datasets


- Knowledge of databases for storing and retrieving data


- Ability to provision and manage virtual machines for machine learning tasks


- Monitoring and logging tools for tracking the performance and health of models


- Understanding of identify and access management for securing cloud resources


- Integration of machine learning workflows into CI/CD pipelines for automated deployment


- Ability to optimize costs associated cloud resources


- Hands on experience with cloud-based ML services for model training, deployment, and management


- Understanding of cloud networking for secure and efficient communication between services


- Proficiency in version control for collaboration and code management


- Excellent communication skills


- Ability to work effectively in a cross-functional team


Education, Certifications, or Special Licenses :

- Master's Degree or Ph.D. in Computer Science, Machine Learning, Applied Mathematics, Engineering or a related field


- 3 to 5 years of training or experience in AI/ML algorithm development


- Experience in technology enhanced learning solution research and development




Other Requirements (Specialized skill sets, behavioral/technical) :


- Experience with Python-based AI/ML frameworks, Java, and/or R


- Experience with ML frameworks (like Keras or PyTorch) and libraries (like scikit-learn)


- Knowledge and practical application of statistical analysis and mathematical modeling concepts and principles


- Excellent communication skills


- Ability to work effectively in a cross-functional team


Functional Areas: Other

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