Machine Learning Engineer
2 months ago
About us:
L&T Technology Services Limited (LTTS) 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 Engineer
Experience Level: 4-5 years
Job Overview:
We are looking for 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:
Model Development and Deployment:
- 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.
Data Processing and Feature Engineering:
- 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.
Model Evaluation and Optimization:
- 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.
Collaboration with Cross-functional Teams:
- Partner with data scientists, software engineers, and product managers to deliver data-driven solutions.
- Translate business requirements into technical specifications for machine learning projects.
Automation and Scalability:
- 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.
Stay Updated:
- 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.
Required Skills and Qualifications:
Education:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, or related field.
Experience:
- 4-5 years of hands-on experience in machine learning, data science, or a related role.
- Experience in designing, training, and deploying machine learning models in production environments.
Technical Skills:
- Strong proficiency in Python, including libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, etc.
- Expertise in machine learning algorithms, statistical modeling, and deep learning.
- Experience with data processing libraries (Pandas, NumPy) and visualization tools (Matplotlib, Seaborn).
- Solid understanding of databases and data warehousing.
Additional Skills:
- Strong problem-solving skills and ability to work in a collaborative environment.
- Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders.
- Experience with MLOps tools for model monitoring, versioning, and pipeline automation (e.g., MLflow, Kubeflow, Airflow) is a plus.
Preferred Qualifications:
- Experience working with big data tools (e.g., Spark, Hadoop) or real-time streaming data (Kafka, Flink).
- Understanding of natural language processing (NLP), computer vision (CV), or reinforcement learning (RL).
- Knowledge of software development best practices, including version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).
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Thanks
Team HR
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