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Machine Learning Engineer

The Customization GroupBengaluru, Karnataka, India

30+ days ago

Job description

We are Make IT Real Tech !

An information technology firm that provides consulting services in IT, software, and advanced areas such as Artificial Intelligence. Our global team of experts is committed to creating AI-driven workflows and solutions that enhance efficiency across the manufacturing, supply chain management, and e-commerce space. By leveraging latest technologies, we offer customized IT solutions that place us at the forefront of innovation, driving advancements in both customer engagement and operational efficiency.

We have a brand-new opportunity for a Machine Learning Engineer.

In this role, you will work on the full ML lifecycle, from data pipeline development to model deployment and monitoring in production environments. Sounds good? Then keep reading!

Why you will love working with us :

Global Collaboration : Gain international experience by working with globally distributed teams
Flexible Work Options : Enjoy remote or hybrid work arrangements that suit your lifestyle
Work-Life Balance : Flexible working hours help you balance your professional and personal life
Private Health Insurance : Comprehensive coverage for your peace of mind
Extra Leave : Additional paid leave for special occasions
Growth Opportunities : Access to valuable knowledge and experience to support your career development
Team Building : Connect with colleagues through team-building activities and company events
Innovation and AI : Be part of an AI-first workplace that enables everyone to drive unique business solutions through state-of-the-art technology

Key Responsibilities :

Model Development & Implementation

Design, develop, and implement machine learning models for various business applications including recommendation systems, classification, and prediction tasks

Conduct experiments to evaluate different modeling approaches and select optimal solutions based on performance metrics and business requirements

Transform proof-of-concept models into production-ready systems with appropriate error handling and scalability

Data Engineering & Pipeline Development

Build robust data pipelines for feature engineering, model training, and inference

Implement data quality checks and monitoring systems to ensure reliable model inputs

Optimize data processing workflows for efficiency and cost-effectiveness

Production Systems & Infrastructure

Deploy models to production using containerization and orchestration tools

Implement model versioning, A / B testing frameworks, and rollback capabilities

Design and maintain model monitoring systems to track performance, detect drift, and trigger retraining

Collaborate with platform teams to ensure models meet latency, throughput, and reliability requirements

Cross-functional Collaboration

Partner with product managers and business stakeholders to understand requirements and translate them into ML solutions

Work with data ETL engineers and BI analysts to ensure proper data flow and model integration

Collaborate with software engineers to integrate ML systems into existing applications

Document technical designs, model architectures, and deployment procedures

Required Qualifications :

Education & Experience

Bachelor's degree in computer science, Engineering, Mathematics, or related technical field, or equivalent practical experience

3+ years of experience building and deploying machine learning systems in production environments

Demonstrated experience with the complete ML project lifecycle from problem formulation to production deployment

Technical Skills

Strong programming skills in Python and proficiency with ML frameworks (TensorFlow, PyTorch, or JAX)

Experience with AWS cloud platform and its ML services (SageMaker, Lambda, EC2, S3)

Experience with MLOps tools and practices including experiment tracking, model registries, and CI / CD for ML

Strong understanding of software engineering principles including version control, testing, and code review practices

Experience with containerization (Docker) and familiarity with orchestration concepts

Machine Learning Expertise

Solid understanding of ML fundamentals including supervised and unsupervised learning, feature engineering, and model evaluation

Experience with deep learning architectures and their practical applications

Knowledge of model optimization techniques including quantization, pruning, and distillation

Understanding of common production ML challenges such as data drift, model degradation, and online learning

Embrace the opportunities that await you here!

Your journey may lead to new skills, relationships, and success.

One team. Millions of happy customers worldwide. Join us! https : / / www.thecustomizationgroup.com /

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Machine Learning Engineer • Bengaluru, Karnataka, India

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