Machine Learning Engineer

Job Description

Responsibilities:

Collaborate with cross-functional teams to understand business requirements and translate them into machine learning solutions.
Develop, train, and deploy machine learning models for real-world applications.
Work with large datasets, ensuring data quality and implementing efficient data preprocessing pipelines.
Utilize ML/DL frameworks to build scalable and high-performance models for both training and inferencing.
Implement and optimize machine learning algorithms for deployment in production environments.
Stay abreast of the latest developments in machine learning and artificial intelligence to ensure the adoption of best practices and emerging technologies.
Collaborate with software developers to integrate machine learning models into existing systems.
Maintain documentation for all aspects of the machine learning pipeline, including data preprocessing, model training, and deployment.
Skills:

Proficiency in Python for data manipulation, analysis, and model development.
Experience with containerization technologies such as Kubernetes and Docker.
Strong understanding of machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch).
Hands-on experience in both model training and inferencing.
Familiarity with Big Data technologies and frameworks.
Basic knowledge of MERN stack (MongoDB, Express.js, React, Node.js) is a plus.
Excellent problem-solving and critical-thinking skills.
Strong communication and collaboration skills.
Experience:

Minimum of 2 years of experience in machine learning engineering.
Proven track record of successfully developing and deploying machine learning models in a production environment.
Experience working with cross-functional teams in an agile development environment.