Lakshmikumaran and Sridharan | Machine Learning Engineer | delhi
2 weeks ago
We are passionate about leveraging cutting-edge technologies to drive business solutions. The ideal candidate will have extensive experience in machine learning, deep learning, and a proven track record of implementing and deploying machine learning models in real-world applications, with a strong emphasis on MLOps practices.
Responsibilities:
Lead the design, development, and deployment of machine learning models for various business applications.
Implement MLOps practices to streamline the end-to-end machine learning lifecycle, including model development, testing, deployment, and monitoring.
Collaborate with cross-functional teams to understand business requirements and translate them into scalable machine learning solutions.
Conduct exploratory data analysis, feature engineering, and model selection to optimize performance.
Implement and deploy machine learning models in production environments, ensuring scalability, reliability, and maintainability.
Stay current with advancements in machine learning and MLOps, identifying opportunities to apply new techniques to business challenges.
Mentor and provide guidance to junior members of the machine learning team.
Collaborate with software engineers to integrate machine learning models into existing systems.
Requirements:
Proven experience as a Senior Machine Learning Engineer with a strong portfolio of successful machine learning projects.
In-depth knowledge of machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
Expertise in MLOps practices, including model versioning, continuous integration, automated testing, and model monitoring.
Experience with deep learning techniques, including neural networks and convolutional neural networks (CNNs).
Proficient in programming languages such as Python and familiarity with data manipulation libraries.
Strong understanding of data preprocessing, feature engineering, and model evaluation.
Experience deploying machine learning models in production environments.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for scalable model deployment.
Excellent problem-solving skills and attention to detail.
Qualifications:
BE/Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
5+ years of experience in machine learning with a focus on practical application and deployment.
5+ years of hands-on experience with popular machine learning frameworks.
Preferred Skills:
Experience with natural language processing (NLP) and computer vision.
Familiarity with distributed computing and parallel processing.
Knowledge of reinforcement learning concepts.
Strong communication skills and the ability to explain complex concepts to non-technical stakeholders.
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