Machine Learning Engineer

Responsibilities

• Develop, deploy, and optimize machine learning and AI solutions addressing complex business challenges
• Create multi-agent systems and equip AI models with function/tool-calling capabilities
• Design and implement RAG systems to ground AI responses in enterprise data
• Assess and integrate AI models (e.g. LLMs) ensuring optimal performance and reliability
• Test and optimize system prompts and few-shot examples for accurate, consistent, and safe AI outputs
• Collaborate with platform teams, data engineers, and data scientists to integrate ML solutions

Requirements

• Bachelor's or Master's in Data Science, Computer Science, Mathematics, Statistics, or related field
• Strong Python programming skills with TensorFlow or PyTorch
• Proven experience working with Large Language Models (LLMs)
• Good understanding of AI agents, agentic workflows, LLM orchestration frameworks, and reasoning patterns
• Experience with data preprocessing, feature engineering, model selection and evaluation
• Minimum 3-6 years of relevant experience in machine learning, data science, or related field
• Personal Skills
• Strong problem-solving and analytical skills with critical and creative thinking
• Excellent communication and collaboration skills across cross-functional teams
• Continuous learning mindset with passion for AI/ML advancements
• Attention to detail and commitment to high-quality, maintainable code
• About MARVES Consulting
• As we grow, we seek talented professionals who are ready to be challenged, contribute meaningfully, and develop their careers in a dynamic environment where great work is recognised.
• If this sounds like you, we'd love to hear from you.
• Please apply and fill the test for the MLL position here :
• https://marves-group.com/assess?role=ml

Additional Information

Role Overview We are seeking a skilled Machine Learning Engineer to join one of our agile development teams in our ML & AI ART. You will play a key part in designing, building, and maintaining robust, scalable AI solutions within a DevOps environment, contributing across the entire lifecycle - from concept to deployment.

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