Senior Machine Learning Engineer

Role Overview

• Designing and developing AI/ML capabilities that power core platform functionality
• Building and deploying machine learning systems end-to-end, from experimentation to production
• Working on problems related to: Natural Language Processing (NLP), Intelligent document processing, Semantic search and matching, Information extraction and classification, Web data parsing and enrichment
• Experimenting with modern AI techniques, LLMs, and agent-based workflows to improve product capabilities
• Training, evaluating, and optimizing models with a focus on scalability, performance, and reliability
• Collaborating closely with engineers, product stakeholders, and founders to iterate quickly and deliver impactful solutions
• Contributing to AI development standards, tooling, testing practices, and internal processes
• Helping balance innovation with pragmatic engineering decisions in a fast-paced environment

Requirements

• 3+ years of experience working as a Machine Learning Engineer or AI Engineer in product-focused environments
• Strong Python development experience in production systems
• Hands-on experience building AI-driven solutions using: LLMs, Prompt engineering, Fine-tuning techniques, Conversational AI, Multi-agent systems/frameworks
• Solid understanding of modern machine learning and NLP concepts
• Experience deploying and maintaining ML systems in production environments
• Strong problem-solving mindset with the ability to work independently and take ownership
• Comfortable operating in ambiguous, fast-changing startup environments
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or a related field

Tech Stack

• Python

Benefits

• High ownership and direct impact on product and technical direction
• Opportunity to shape the AI architecture and engineering culture early on
• Work alongside experienced founders and high-performing engineers
• Fast iteration cycles and exposure to cutting-edge AI technologies
• Product-centric environment where engineering work directly influences user value
• Strong focus on innovation, experimentation, and continuous improvement