Our AI vision

AI is not just part of our product—it is our product. We’re creating autonomous agents that understand HR workflows, interact naturally with users, and deliver measurable business impact.

We see large language models (LLMs) as the foundation, but success comes from making them robust, reliable, and enterprise-ready. That means combining research, engineering, and product thinking to deliver AI features that work at scale in mission-critical environments.

As an AI engineer, you will sit at the intersection of ML research and software engineering. You’ll work on everything from prompt design and evaluation pipelines to integrating AI models into production systems and making them safe, fast, and scalable.

What you will do

• Build AI features: Design and implement end-to-end AI features that power Maki’s HR agents, from prototyping to production.

• Experiment with LLMs: Test, fine-tune, and evaluate cutting-edge models (open-source and commercial) to deliver the best mix of performance, cost, and safety.

• Develop evaluation pipelines: Build frameworks to measure accuracy, reliability, bias, and business impact of AI-driven features.

• Optimize for scale: Work on latency, caching, and cost-optimization strategies to make AI features enterprise-ready.

• Ensure safety & compliance: Collaborate with the security and product teams to ensure AI features meet enterprise standards for privacy, fairness, and reliability.

• Collaborate cross-functionally: Partner with product managers, designers, and engineers to turn ideas into shipped features.

• Stay ahead: Explore new AI research, tools, and frameworks to keep Maki at the cutting edge.

Who we’re looking for

• Engineering background: Strong foundation in computer science, machine learning, or a related field.

• Technical skills: Proficient in Python; comfortable with modern ML frameworks (PyTorch, TensorFlow, Hugging Face).

• Hands-on with LLMs: Experience working with APIs (OpenAI, Anthropic, Cohere, etc.) or fine-tuning open-source models.

• Evaluation mindset: You care about rigor—measuring and improving model outputs, not just building prototypes.

• Problem-solver: Pragmatic and creative in turning research ideas into production features.

• Mindset: Curious, collaborative, and eager to push boundaries in applied AI.

Bonus points if you:

• Have experience deploying AI systems in production environments.

• Have worked with RAG pipelines, vector databases, or agentic frameworks.

• Are familiar with enterprise SaaS requirements (latency, cost, observability).

• Have contributed to open-source AI projects or published applied ML work.

• Intro call – 30 min
  Screening with Ben (Cofounder). A first conversation to get to know you and share more context on Maki and the role.

• Technical case – 90 min
  With the AI team. You’ll prototype a feature or solve a real-world AI challenge, then walk us through your thinking.

• Founder interview – 30 min
  Meet one of our founders to validate culture and values fit.

• Final wrap-up
  Offer call (and ideally, a celebration!).