Senior Machine Learning Engineer - Responsible AI

About the role

Atlassian is looking for a Senior Machine Learning Engineer to join its Responsible AI (RAI) & AI Safety engineering team, expanding from the USA, Australia and New Zealand to India. The team builds, operates and advances centralized AI safety, content moderation and guardrail platforms that protect users from jailbreaks, prompt injection, harmful content, bias and policy violations while keeping latency and user experience intact. The role is remote and requires the candidate to be located in India.

Key responsibilities

• Architect, train, fine-tune and deploy ML/LLM-based guardrail and moderation models (text, multi-modal and code) to protect user inputs and model outputs.
• Build offline and online evaluation frameworks, adversarial red-teaming test suites and LLM-as-a-judge pipelines to measure precision, recall and robustness against model drift.
• Optimize safety filtering for real-time serving with low latency (P50/P99 targets) and high throughput, integrated with the central AI Gateway and inference layers.
• Research and build defenses against adversarial prompts, jailbreaks, data leakage, hallucinations and unauthorized tool-calling in agentic systems.
• Support technical readiness for standards such as the EU AI Act, ISO 42001 / AIMS and FedRAMP through verifiable safety controls, audit logging and watermarking.
• Partner with engineering managers, staff engineers, data scientists and product managers, and mentor junior engineers.

Required profile

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science or a related quantitative field, with 7+ years of experience building and deploying ML systems in production.
• Proven experience with rigorous evaluation pipelines and benchmarking datasets for high-stakes classification or safety systems.
• Ability to communicate ML trade-offs clearly to technical and non-technical stakeholders, with strong analytical and problem-solving skills.

Required skills

• NLP and LLM techniques, transformers, prompt engineering, fine-tuning (PEFT/LoRA) and model alignment.
• Python, with familiarity with Kotlin, Java or Go.
• Cloud deployment on AWS or GCP using Kubernetes/Docker and Spark or SQL.
• At least one visualization tool (Tableau, R-Shiny, Looker, etc.).
• Nice to have: inference engine optimization (Triton, vLLM, TensorRT-LLM), content provenance/watermarking, streaming pipelines (Kafka, Kinesis) or graph-based entity systems.

The role may be eligible for benefits, bonuses, commissions and equity. Atlassian states that pay is set within a range based on skills, knowledge and experience.