Principal Machine Learning Systems Engineer (GenAI Products & Knowledge Innovations)
Washington DC, DC
- Pay
Multiple pay statements — pay source
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are: Zone A: $236,700 - $309,025 Zone B: $213,030 - $278,123
Zone A: $236,700 - $309,025 Zone B: $213,030 - $278,123 Zone C: $196,461 - $256,491
Zone B: $213,030 - $278,123 Zone C: $196,461 - $256,491 Qualifications
Read the full posting- Work setup
Remote — work setup source
Work setup in the employer’s listing: TELECOMMUTE
From the employer’s posting- Employment
- Unconfirmed
What you’ll work on
Full postingArchitect systems for training, fine-tuning and serving LLMs and embeddings
Build retrieval, hybrid search and RAG pipelines on knowledge data
Turn proof-of-concept systems into reliable, scalable services
Optimize latency, throughput and resource efficiency for GenAI workloads
Build tools and infrastructure for rapid experimentation and evaluation
From the employer’s posting
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.
Build proof-of-concept (POC) systems and evolve them into reliable, scalable services.
Optimize latency, throughput, and resource efficiency for GenAI workloads.
Develop tools and infra to support rapid experimentation, evaluation, and deployment of prototypes.
What you’ll bring
All qualificationsCore experience
- 6+ years in ML systems engineering, backend engineering, or infrastructure roles.
- Familiarity with search/GenAI evaluation metrics (e.g., NDCG, groundedness, latency benchmarks).
- Experience with large-scale model training, inference pipelines, or search/retrieval systems.
- Experience with monitoring, observability, and reliability practices for ML systems.
- Proficiency in backend systems and ML frameworks (Python, PyTorch, TensorFlow, Hugging Face).
- Experience with vector databases (Weaviate, Pinecone, FAISS), orchestration frameworks (LangChain, LlamaIndex).
Qualification wording
6+ years in ML systems engineering, backend engineering, or infrastructure roles.
Familiarity with search/GenAI evaluation metrics (e.g., NDCG, groundedness, latency benchmarks).
Experience with large-scale model training, inference pipelines, or search/retrieval systems.
Experience with monitoring, observability, and reliability practices for ML systems.
Proficiency in backend systems and ML frameworks (Python, PyTorch, TensorFlow, Hugging Face).
Experience with vector databases (Weaviate, Pinecone, FAISS), orchestration frameworks (LangChain, LlamaIndex).
Education & alternatives
📚 Education - Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent industry experience. Nice to Have
Tools in this posting
- Python
- AWS
- Azure
- Docker
- Google Cloud (GCP)
- Kubernetes
- Huggingface
- PyTorch
- TensorFlow
Source — Tool mentions in context
💡 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
Benefits in the posting
Full benefits wording- 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.
From the employer’s posting.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 15, 2026 · 33d ago
- Recorded sightings
- 65
- Last seen by us
- Oct 17, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Job description
Overview
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.
Working at Atlassian
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Responsibilities
What You'll 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.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $236,700 - $309,025
Zone B: $213,030 - $278,123
Zone C: $196,461 - $256,491
Qualifications
What We're 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, we're 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 everyone's 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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on careers-americas.icims.com. The employer’s form will show what is required.
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Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are: Zone A: $236,700 - $309,025 Zone B: $213,030 - $278,123
More source context
Zone A: $236,700 - $309,025 Zone B: $213,030 - $278,123 Zone C: $196,461 - $256,491
More relevant text appears in the full description.
- Location & working pattern
Washington DC, DC
- 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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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