ML Engineer

This role is for one of Weekday's clients

JobType: full-time

Requirements

We're looking for a Machine Learning Engineer to join as an early team member and help shape the foundation of our AI-powered platform. You'll work directly with the founding team — serial entrepreneurs with a track record of building and exiting successful startups — to design, build, and scale real-world AI systems that transform how global brands approach marketing.

This isn't a "maintenance" role — it's a builder's role. You'll have full ownership of the machine learning infrastructure, from data ingestion and model training to deployment and optimization. You'll work on cutting-edge problems around LLMs, embeddings, reasoning frameworks, and feedback loops, developing systems that continuously learn and improve through user interactions.

If you thrive in zero-to-one environments, love rapid experimentation, and want to see your work make a direct business impact, this is the place for you.

Key Responsibilities

• Own the ML lifecycle end-to-end — from data pipelines and model design to deployment, monitoring, and optimization in production.
• Build, fine-tune, and scale LLM-based systems using APIs and open-source frameworks for natural language understanding, summarization, and reasoning.
• Develop and maintain embeddings, feedback loops, and decision engines that power intelligent marketing automation.
• Collaborate with product, design, and engineering teams to translate user problems into ML-driven solutions.
• Prototype quickly and iterate fast, applying real-world feedback to improve performance and accuracy.
• Implement best practices in data versioning, model validation, and CI/CD pipelines for ML workflows.
• Optimize ML models for performance, latency, and scalability across distributed systems.
• Stay ahead of industry trends in AI agents, reinforcement learning, and applied ML in marketing.
  
  

What You Bring

• 3-5 years of hands-on experience in machine learning engineering or applied AI development.
• Strong proficiency in Python, with experience using PyTorch, TensorFlow, or JAX.
• Experience with LLM APIs (OpenAI, Anthropic, Hugging Face, etc.) and building products powered by foundation models.
• Proven track record of building and shipping ML systems to production — not just research or notebooks.
• Deep understanding of data processing, model optimization, and scalable architectures.
• Ability to work independently in fast-paced, ambiguous environments.
• A growth mindset — curiosity, experimentation, and an obsession with learning new technologies.
  
  

Bonus Skills

• Experience with AI agent systems or reasoning frameworks.
• Background in eCommerce, martech, or personalization engines.
• Understanding of UX/design-driven development and how AI can elevate user experience.
• Familiarity with vector databases, LangChain, and retrieval-augmented generation (RAG) frameworks.