We are seeking a talented Machine Learning Engineer to design, develop and deploy scalable Machine Learning models and algorithms that drive business value. The ideal candidate will have a strong background in Mathematics, Statistics, and Computer Science, as well as experience in building end-to-end Machine Learning systems. The candidate will collaborate closely with Data Scientists, AI Developers, and Software Engineers to design, develop, test, and deploy Machine Learning models in a production environment.
Key Responsibilities:
- Develop, test, and deploy Machine Learning models and algorithms that solve complex business problems.
- Collaborate with Data Scientists, AI Developers, and Software Engineers to design, develop, and deploy end-to-end Machine Learning systems.
- Build scalable and efficient Machine Learning pipelines using distributed computing and Big Data technologies.
- Optimize Machine Learning models and algorithms for performance, accuracy, and reliability.
- Evaluate and implement state-of-the-art Machine Learning and Deep Learning algorithms and frameworks.
- Develop and maintain documentation for Machine Learning models and algorithms.
- Identify and solve technical and operational issues related to Machine Learning models in a production environment.
- Stay up-to-date with the latest Machine Learning and Deep Learning research and developments.
Requirements
Qualifications:
- Bachelors or Masters degree in Computer Science, Mathematics, Statistics, or related field.
- 3+ years of experience in Machine Learning development and deployment.
- Strong proficiency in programming languages such as Python, Java, or C++.
- Experience with Machine Learning frameworks like TensorFlow, Keras, or PyTorch.
- Experience with Big Data technologies like Hadoop, Spark, or Hive.
- Strong understanding of Mathematics, Statistics, and Probability theory.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration skills.
Preferred Qualifications:
- PhD in Computer Science, Mathematics, Statistics, or related field.
- Experience with Natural Language Processing (NLP) or Computer Vision (CV).
- Experience with Cloud-based Machine Learning services like AWS SageMaker, Azure Machine Learning, or Google Cloud AI Platform.
- Experience with containerization technologies like Docker and Kubernetes.
As a Machine Learning Engineer, you will play a critical role in building scalable and efficient Machine Learning systems that drive business value. If you have a passion for Machine Learning and enjoy solving complex problems, we encourage you to apply for this exciting opportunity.
Qualifications: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field. 3+ years of experience in Machine Learning development and deployment. Strong proficiency in programming languages such as Python, Java, or C++. Experience with Machine Learning frameworks like TensorFlow, Keras, or PyTorch. Experience with Big Data technologies like Hadoop, Spark, or Hive. Strong understanding of Mathematics, Statistics, and Probability theory. Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Preferred Qualifications: PhD in Computer Science, Mathematics, Statistics, or related field. Experience with Natural Language Processing (NLP) or Computer Vision (CV). Experience with Cloud-based Machine Learning services like AWS SageMaker, Azure Machine Learning, or Google Cloud AI Platform. Experience with containerization technologies like Docker and Kubernetes. As a Machine Learning Engineer, you will play a critical role in building scalable and efficient Machine Learning systems that drive business value. If you have a passion for Machine Learning and enjoy solving complex problems, we encourage you to apply for this exciting opportunity.