Job Description

Assistant ManagerEXL/AM/1476330


Global TechnologyNoida
Posted On
09 Sep 2025
End Date
24 Oct 2025
Required Experience
4 - 6 Years



Basic Section
Number Of Positions


1


Band


B1


Band Name


Assistant Manager


Cost Code


D014176


Campus/Non Campus


NON CAMPUS


Employment Type


Permanent


Requisition Type


New


Max CTC


0.0000 - 0.0000


Complexity Level


Not Applicable


Work Type


Hybrid - Working Partly From Home And Partly From Office


Organisational
Group


Enabling


Sub Group


Global Technology


Organization


Global Technology


LOB


Global Technology


SBU


Global Technology


Country


India


City


Noida


Center


Noida - Center V




Skills
Skill


PYTHON AUTOMATION


PYTHON PROGRAMMING


MACHINE LEARNING


API DESIGN


Minimum Qualification


B.TECH/B.E


Certification


No data available

Job Title:

Python & Machine Learning Developer

Experience:

4-6 Years

Location:

Bengaluru/ Noida/Pune (Hybrid/Remote options available)

Role Overview

We are seeking a highly skilled Python & Machine Learning Developer to join our dynamic team. In this role, you will design, develop, and deploy machine learning models and data pipelines to address complex business challenges. You will also leverage your strong Python programming expertise to build automation scripts and tools that enhance efficiency. Collaboration with cross-functional teams to deliver scalable, cloud-enabled, and automated solutions is key to this role.

Key Responsibilities

Strong Python Development:

Write clean, efficient, and maintainable Python code to build machine learning models, data processing scripts, and automation tools.

Model Development:

Design, implement, and optimize machine learning models using Python libraries such as scikit-learn, TensorFlow, and PyTorch.

Automation:

Develop automation workflows and scripts using Python to streamline data ingestion, preprocessing, model training, deployment, and monitoring.

Data Pipeline Engineering:

Build and maintain robust data pipelines for data ingestion, preprocessing, and transformation to support model training and deployment.

Cloud Integration:

Deploy and manage ML models and data workflows on cloud platforms, primarily AWS, ensuring scalability and reliability.

Algorithm Optimization:

Apply statistical and machine learning techniques to analyze large datasets, identify patterns, and develop predictive models.

Generative AI:

Assist in exploring and integrating basic Generative AI capabilities into existing or new solutions.

Collaboration:

Work closely with data engineers, analysts, and business stakeholders to understand requirements and deliver actionable insights.

Deployment & Monitoring:

Deploy machine learning models into production environments and monitor their performance to ensure reliability and accuracy.

Documentation & Reporting:

Maintain comprehensive documentation of code, processes, and model performance metrics. Present findings and recommendations to stakeholders.

Required Skills & Qualifications

Education:

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.

Strong Python Programming:

Proven expertise in Python programming with an emphasis on writing robust, scalable, and reusable code.

Automation:

Experience in developing automation scripts and tools using Python to improve workflows and operational efficiency.

Machine Learning:

Strong understanding of machine learning algorithms, model evaluation metrics, and feature engineering techniques.

Cloud Platforms:

Hands-on experience with AWS services such as S3, EC2, SageMaker, Lambda, and related tools for ML deployment and data processing.

Generative AI:

Basic familiarity with Generative AI concepts and tools (e.g., GPT models, diffusion models).

Data Handling:

Experience with data preprocessing, data wrangling, and working with structured and unstructured data.

SQL:

Proficient in SQL for data querying, transformation, and integration with machine learning workflows.

Version Control:

Familiarity with Git and collaborative development workflows.

Communication:

Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Preferred Skills

Advanced Techniques:

Knowledge of deep learning, natural language processing (NLP), or time series forecasting.

DevOps Practices:

Familiarity with CI/CD pipelines and containerization technologies like Docker and Kubernetes.

Business Acumen:

Ability to translate business problems into analytical solutions and effectively communicate findings.
Workflow
Workflow Type


Digital Solution Center