Principal Machine Learning Systems Engineer (GenAI Products & Knowledge Innovations)
About The Position
At Atlassian, we’re on a mission to unleash the potential of every team. As part of that mission, we're investing deeply in Generative AI — pioneering advanced modeling and rapid innovations that accelerate how teams work, discover, and create. We’re seeking a Principal Machine Learning Systems Engineer (P60) to lead technical directions of GenAI Products & Knowledge Innovations in US. You’ll focus on building and scaling the systems that power advanced GenAI products with enterprise knowledge, rapid prototyping, and applied research—bridging cutting-edge algorithms with reliable, high-performance infrastructure.
Requirements
- 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.
- 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).
- Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent industry experience.
Nice To Haves
- 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.
Responsibilities
- 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.
- 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.
- 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.
Benefits
- health and wellbeing resources
- paid volunteer days
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What This Job Offers
Job Type
Full-time
Career Level
Principal
