Machine learning engineer
3 weeks 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 Tensor Flow, Py Torch, Scikit-learn, Keras, etc.
Expertise in machine learning algorithms, statistical modeling, and deep learning.
Experience with data processing libraries (Pandas, Num Py) 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).
-- Thanks Team HR
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