Machine Learning Engineer
3 weeks ago
L&T Technology Services is a global leader in Engineering and R&D (ER&D) services. With 816 patents filed for 57 of the Global Top 100 ER&D spenders, LTTS lives and breathes engineering and technology. Our innovations speak for themselves – World's 1st Autonomous Welding Robot, Solar 'Connectivity' Drone, and the Smartest Campus in the World, to name a few.
Job Title: Machine Learning EngineerExperience Level: 4-5 years
Job Overview:We are seeking a skilled Machine Learning Engineer to join our team and help design, implement, and maintain cutting-edge machine learning models that drive insights, automation, and product improvements. You will collaborate with software engineers, and product teams to develop scalable ML solutions for real-world problems. Your expertise will contribute to building end-to-end machine learning pipelines and improving model performance across various projects.
Key Responsibilities:- Design, implement, and optimize machine learning models using techniques like regression, classification, clustering, and deep learning.
- Build end-to-end machine learning pipelines, from data collection to model deployment.
- Collaborate with data engineers to acquire, preprocess, and clean large-scale datasets.
- Design and implement feature extraction, transformation, and selection methods to improve model performance.
- Use metrics like accuracy, precision, recall, F1-score, ROC-AUC, and others to evaluate model performance.
- Perform hyperparameter tuning, cross-validation, and model debugging to enhance accuracy and efficiency.
- Partner with data scientists, software engineers, and product managers to deliver data-driven solutions.
- Translate business requirements into technical specifications for machine learning projects.
- Develop scripts and tools to automate data processing, model training, and evaluation pipelines.
- Work on scaling models and optimizing runtime performance for large datasets and real-time applications.
- Keep up to date with the latest advancements in machine learning, AI, and relevant technologies.
- Experiment with emerging techniques like transfer learning, reinforcement learning, and generative models.
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