Principal Machine Learning Systems Engineer, GenAI Products & Knowledge Innovations (Remote)

What Youll Do

🛠 Design and Build ML Systems

• Architect and implement scalable systems for training, fine-tuning, and serving large language models and embeddings.

• Build efficient retrieval, hybrid search, and RAG pipelines integrated with knowledge-grounded data.

• Develop tools and infra to support rapid experimentation, evaluation, and deployment of prototypes.

⚡ Enable Rapid Prototyping & Applied Research

• Partner with applied scientists to bring new ideas to life in robust, production-ready pipelines.

• Build proof-of-concept (POC) systems and evolve them into reliable, scalable services.

• Optimize latency, throughput, and resource efficiency for GenAI workloads.

🤝 Collaborate Across Disciplines

• Work closely with ML engineers, backend developers, and product teams to ship end-to-end innovations.

• Contribute to best practices in model deployment, monitoring, and evaluation.

• Help establish the team as a world-class hub for GenAI systems innovation.

What Were Looking For

✅ Experience

• 6+ years in ML systems engineering, backend engineering, or infrastructure roles.

• Strong track record of building and scaling ML-powered services in production.

• Experience with large-scale model training, inference pipelines, or search/retrieval systems.

💡 Skills

• Proficiency in backend systems and ML frameworks (Python, PyTorch, TensorFlow, Hugging Face).

• Experience with vector databases (Weaviate, Pinecone, FAISS), orchestration frameworks (LangChain, LlamaIndex).

• Strong coding skills and ability to optimize systems for performance and reliability.

• Familiarity with cloud environments (AWS, GCP, Azure) and container/orchestration tools (Kubernetes, Docker).

📚 Education

• Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent industry experience.

Nice to Have

• Background in distributed systems, high-performance computing, or GPU optimization.

• Familiarity with search/GenAI evaluation metrics (e.g., NDCG, groundedness, latency benchmarks).

• Experience with monitoring, observability, and reliability practices for ML systems.

• Contributions to open-source infra or ML systems frameworks.

Benefits & Perks

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.

About Atlassian

At Atlassian, were motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyones perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

To learn more about our culture and hiring process, visit go.atlassian.com/crh.

In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.