800000 - 1300000 INR - Yearly
Bangalore, Karnataka, India
Information Technology
Full-Time
SourcingXPress
Overview
Company: KGIS
Website: Visit Website
Business Type: Consulting Firm
Company Type: Service
Business Model: B2B
Funding Stage: Bootstrapped
Industry: IT consulting
Salary Range: ₹ 8-13 Lacs PA
Job Description
Role Overview:
We are looking for a Machine Learning Engineer to develop and implement cutting-edge machine learning algorithms and models. The ideal candidate will leverage expertise in machine learning, data analysis, and software engineering to deliver innovative solutions that solve complex problems and drive business growth.
Key Responsibilities
Website: Visit Website
Business Type: Consulting Firm
Company Type: Service
Business Model: B2B
Funding Stage: Bootstrapped
Industry: IT consulting
Salary Range: ₹ 8-13 Lacs PA
Job Description
Role Overview:
We are looking for a Machine Learning Engineer to develop and implement cutting-edge machine learning algorithms and models. The ideal candidate will leverage expertise in machine learning, data analysis, and software engineering to deliver innovative solutions that solve complex problems and drive business growth.
Key Responsibilities
- Develop and implement machine learning algorithms and models to solve business problems and optimize processes.
- Collaborate with data scientists, software engineers, and product managers to define project requirements and deliver solutions.
- Design and implement scalable data pipelines for pre-processing, feature engineering, and model training.
- Conduct exploratory data analysis and feature extraction to uncover insights and patterns in large datasets.
- Evaluate and benchmark machine learning models using appropriate metrics and techniques.
- Optimize and fine-tune machine learning models for performance, scalability, and reliability.
- Stay current with the latest advancements in machine learning research and technology.
- Mentor junior team members and guide best practices in machine learning and data science.
- 4–7 years of professional experience in machine learning, data science, or related roles.
- Strong exposure to time series modeling using ARIMA, ARIMAX.
- Understanding of underfitting and overfitting, and techniques to generalize models.
- Knowledge of regularization techniques: LASSO, RIDGE, ELASTIC NET, and when to apply them.
- Experience with unsupervised learning: clustering, dimensionality reduction, outlier detection.
- Understanding of model optimization techniques, including Gradient Descent.
- Knowledge of deep learning algorithms: CNN, RNN, LSTM, and methods to control overfitting.
- Hands-on experience in data engineering for large-scale data using Big Data tools (Spark, Hive).
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