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# Machine Learning Engineer

- **Company:** Atlas Data Systems, L. L.C.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $206,100.0 - $269,075.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Files, Machine Learning, Performance Tuning, Systems Architecture, Large Language Models, Multi-Agent Systems, Model Validation, Data Strategy, Low Latency, Atlassian Tools
- **Published:** September 10, 2026
- **Apply:** https://www.themuse.com/jobs/atlassian/senior-machine-learning-engineer-e438da

## About the Role

* A track record of architecting and shipping large-scale ML or AI systems that deliver measurable customer and business impact.
 * Deep experience with LLM-powered products, agentic systems, model evaluation, experimentation, and dataset development.
 * Strong production engineering skills and the ability to remain hands-on in a modern ML stack.
 * Technical leadership: setting direction, influencing across teams, and leading complex initiatives from ambiguity to production.
 * Excellent product and technical judgment, including balancing quality, speed, reliability, safety, latency, and cost.
 * The ability to communicate complex ideas clearly and raise the effectiveness of engineers around you through mentorship and technical leadership.

## Description

As a Senior Machine Learning Engineer, you'll tackle the open-ended technical problems that determine whether customers trust Rovo with increasingly complex and consequential work. You'll remain deeply hands-on while setting direction across teams: driving advances in models, agents, and evaluation and turning them into measurable improvements for millions of active users.

 * Architect and build production ML and evaluation systems that operate at scale, including datasets, simulations, automated judges, regression suites, experimentation platforms, and online quality signals.
 * Advance the state of Rovo's agentic capabilities across reasoning, planning, tool selection and use, action correctness, retrieval, memory, and long-horizon execution.
 * Close the loop between evaluation and product impact: identify systemic failure modes, develop interventions, ship them to production, and establish whether they improved customer outcomes.
 * Make high-leverage technical decisions across model choice, prompting, fine-tuning, data strategy, system architecture, and inference; balancing quality with latency, reliability, safety, and cost.
 * Lead ambitious, cross-organizational initiatives with ML, engineering, product, analytics, research, and design partners, creating clarity and momentum where neither the problem nor the solution is well defined.
 * Establish reusable methods, systems, and quality standards that raise the bar not only for Rovo Chat, but for AI-powered experiences across Atlassian.
 * Multiply the impact of other engineers through technical leadership, design reviews, mentorship, and a compelling long-term vision for how we build and evaluate world-class AI products., 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.


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