Help build AI products by architecting, building, training and deploying models.
Collaborate with product and design teams to experiment and ship fast.
Participate in code reviews and technical discussions, sharing knowledge and shaping engineering standards.
Own full AI generation pipelines: data prep/labeling, model selection and fine-tuning.
Build and maintain data pipelines to ensure clean, reliable, and scalable training datasets.
Evaluate and integrate third-party AI services and APIs to accelerate development.
Deploy, monitor, and continuously improve model performance, accuracy and costs.
Conduct experiments to evaluate new features, algorithms, architectures, or approaches.
Document workflows, share insights, and contribute to best practices in applied machine learning.

Requirements

2+ years shipping production features.
Strong Python for ML and working knowledge of TypeScript.
Experience with LLMs (fine-tuning, prompt engineering, evaluation).
Understanding of ML fundamentals (training/validation/test splits, overfitting, metrics like precision/recall).
Hands-on experience with structured data extraction from unstructured sources.
AWS cloud experience.
Nice to Have: Built agentic systems (e.g., LangGraph, Bedrock Agents/AgentCore, OpenAI Agents SDK) and/or MCP servers.
Experience with model quantization and optimization techniques.
MLOps: experiment tracking, model/version management, A/B or shadow testing, rollback strategies.
Experience building real-time voice features: speech recognition, conversational flow.
Experience with vector databases and RAG implementation.
Knowledge of prompt chaining and few-shot learning techniques.
Data privacy & security for AI workloads (PII handling, auditability, least-privilege IAM).

Benefits

Competitive, performance-based remuneration
Equity options - own a piece of what you’re helping to build
20 days of paid annual leave, plus sick, carer’s, and compassionate leave
Paid parental leave - 16 weeks for primary carers, 6 weeks for secondary carers (including adoption and stillbirth support)
Professional growth budget and a transparent career development framework
Laptop and home-office setup budget
Flexible work - remote or hybrid, plus the ability to work from anywhere for a few weeks each year
Community & connection - weekly team lunches, global offsites, and our signature “Life Story” sessions

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonTypeScriptLLMsmodel fine-tuningstructured data extractionAWSmodel quantizationMLOpsspeech recognitionvector databases

Soft Skills

collaborationknowledge sharingtechnical discussiondocumentationexperiment evaluation