Machine Learning Engineer

Make IT Real Tech

global team

AI-driven

enhance efficiency

e-commerce

customized IT solutions

Machine Learning Engineer.

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
  

One team. Millions of happy customers worldwide. Join us!