ML Engineer — Fresh Talent (Faisalabad) | Visa Included

UrbanForm Developments; Punjab; On-site; PKR 3,948,000 - 5,342,000; Full time

Benefits offered by this job

Accommodation provided

Visa support

Job summary

UrbanForm Developments in Faisalabad invites applications for a Machine Learning Engineer to design, develop and implement ML models driving business insights and solutions. You will work with data scientists and software engineers to identify opportunities for applying ML techniques across products and services.

You will perform data cleaning, feature engineering and model training, and run experiments to evaluate performance.

Qualifications

• Bachelor's or Master's in CS, DS or related fields.
• Strong Python or R programming for ML tasks.
• Experience with ML libraries TensorFlow, Keras or PyTorch.
• Experience handling large datasets and SQL data analysis.
• Knowledge of ML techniques (regression, classification, clustering).
• Excellent problem-solving and creative thinking.

Responsibilities

• Develop and implement machine learning algorithms and models to solve complex business problems
• Collaborate with data scientists and software engineers to design, test and deploy machine learning solutions
• Perform data cleaning, feature engineering and model training using various tools and techniques
• Conduct experiments to evaluate model performance and make necessary adjustments
• Communicate technical concepts and findings to non-technical stakeholders in a clear and concise manner

Skills

Python

R

TensorFlow

Keras

PyTorch

SQL

Regression

Classification

Clustering

Problem solving

Education

Bachelor's or Master's degree in CS/DS

Tools

SQL

Job description

UrbanForm Developments in Faisalabad invites applications for a Machine Learning Engineer to design, develop and implement ML models driving business insights and solutions. You will work with data scientists and software engineers to identify opportunities for applying ML techniques across products and services.

You will perform data cleaning, feature engineering and model training, and run experiments to evaluate performance.