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Atlassian

Builds software for team planning and knowledge

Senior Machine Learning Engineer - Responsible AI

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listed

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Machine Learning, Data Science, or a related quantitative field, and 7+ years of industry experience building and deploying machine learning systems in production.
  • Deep hands-on experience with modern natural language processing and large language model techniques, transformer architectures, prompt engineering, fine-tuning such as PEFT/LoRA, and model alignment.
  • Proficiency in Python and familiarity with Kotlin, Java, or Go, with experience writing clean, testable, performant production-grade code.
  • Experience constructing rigorous evaluation pipelines and benchmarking datasets, and managing precision/recall trade-offs for high-consequence classification or safety systems.
  • Expertise in communicating insights with data and familiarity with at least one visualization tool, such as Tableau, R-Shiny, MicroStrategy, SAP BusinessObjects, or Looker.
  • Experience deploying and scaling machine learning services in cloud environments such as AWS or GCP using containerized platforms such as Kubernetes or Docker, and distributed data processing frameworks such as Spark and SQL.
  • Strong analytical problem-solving skills and clear communication skills to explain machine learning trade-offs to technical and non-technical stakeholders.
  • An agile development mindset focused on iteration, solving problems from first principles, and navigating ambiguity.

Responsibilities

  • Architect, train, fine-tune, and deploy machine-learning and large-language-model guardrail and moderation models for text, multimodal content, and code across Atlassian products.
  • Design offline and online evaluation frameworks, adversarial test suites (red-teaming), and LLM-as-a-judge pipelines to measure precision, recall, false-positive rates, and robustness against model drift.
  • Optimize model accuracy and low-latency performance to deliver cost-effective, high-throughput safety filtering integrated with the central AI Gateway and inference layers.
  • Research and build defenses against adversarial prompts, jailbreaks, data leakage, hallucinations, and unauthorized tool-calling behaviors in agentic systems.
  • Support technical readiness for enterprise standards and emerging AI regulations, including the EU AI Act, ISO 42001/AIMS, and FedRAMP, through verifiable safety controls, audit logging, and watermarking capabilities.
  • Partner with engineering managers, staff engineers, data scientists, and product managers to steer technical strategy; provide code and design reviews; and mentor junior engineers across the team.

Desired Qualifications

  • Experience in Trust & Safety, content moderation, or AI red-teaming/adversarial robustness.
  • Hands-on experience optimizing inference engines such as Triton Inference Server, vLLM, or TensorRT-LLM, or using model quantization techniques for low-latency serving.
  • Familiarity with AI governance frameworks, content provenance/watermarking, or regulatory compliance standards such as the EU AI Act, NIST AI RMF, or ISO 42001.
  • Experience with large-scale streaming pipelines such as Kafka or Kinesis, or graph-based entity systems.

About the Company

Atlassian

Builds software for team planning and knowledge

Atlassian builds software that helps businesses and other organizations coordinate projects, document knowledge and manage technology services. Its Jira and Confluence applications give teams shared spaces for tracking tasks and keeping decisions, plans and reference material connected to work. Software developers also use its tools to manage code, while business and IT teams organize requests and automate routine workflows. Customers pay recurring subscriptions for hosted software or self-managed licenses, with pricing linked to users and selected service levels. Atlassian was founded in 2002 and has its headquarters in Sydney, New South Wales, Australia.

Company size
10,001+
Company stage
IPO
Headquarters
Sydney NSW, Australia
Founded
2002

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