Senior Engineer - Machine Learning
San Francisco - United States - San Francisco, California 94104 United States; Remote - Remote
Full Time Senior-level / Expert USD 165K - 265K
Atlassian
Atlassian's team collaboration software like Jira, Confluence and Trello help teams organize, discuss, and complete shared work.Overview
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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Responsibilities
About JSM Team
Jira Service Management is one of the marquee products of Atlassian. Through this solution, we are helping technical and non-technical teams centralize and streamline service requests, respond to incidents, collect and maintain knowledge, manage assets and configuration items, and more. Specifically this team within JSM works on using assitive AI to automate IT operational tasks, troubleshoot problems, and reduce mental overload for oncall engineers and alike. By weaving these capabilities into our product we revolutionise AIOps by moving from a traditional reactive troubleshooting-based system to a proactive problem-solving approach
What you will do
As a Principal Engineer on the JSM team, you will get the opportunity to work on cutting-edge AI and ML algorithms that help modernize IT Operations by reducing MTTR (mean time to resolve), and MTTI (Mean time to identify). You will use your software development expertise to solve difficult problems, tackling complex infrastructure and architecture challenges.
In this role, you'll get the chance to:
Shape the future of AIOps: Be at the forefront of innovation, shaping the next generation of AI-powered operations tools that predict, prevent, and resolve IT issues before they impact our customers
Master Generative AI: Delve into the world of generative models, exploring their potential to detect anomalies, automate responses, and personalize remediation plans
Become a machine learning maestro: Hone your skills in both supervised and unsupervised learning, building algorithms that analyze mountains of data to uncover hidden patterns and optimize system performance
Collaborate with diverse minds: Partner with a brilliant team of engineers, data scientists, and researchers, cross-pollinating ideas and learning from each other's expertise
Make a tangible impact: Your work will directly influence the reliability and performance of Atlassian's critical software, driving customer satisfaction and propelling our business forward.
Routinely tackle complex architectural challenges, spar with principal engineers to build ML pipelines and models that scale for thousands of customers
Lead code reviews & documentation as well as take on complex bug fixes, especially on high-risk problems
Our tech stack is primarily Python/Java/Kotlin built on AWS.
On your first day, we’ll expect you to have
Fluency in Python
Solid understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, and NLP.
Familiarity with popular ML libraries like sci-kit-learn, Keras/TensorFlow/PyTorch, numpy, pandas
Good Understanding of Machine Learning project lifecycle
Experience in architecting and implementing high-performance RESTful microservices ( API development for ML Models )
Familiarity with MLOps and experience with scaling and deploying Machine Learning models
It would be great, but not required if you have
Experience with cloud-based machine learning platforms (e.g., AWS SageMaker, Azure ML Service, Databricks).
Experience with MLOps tools ( MLflow, Tecton, Pinecone, Feature Stores )
Experience with AIOps or related fields like IT automation or incident management.
Experience building and operating large-scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking).
Experience with using OpenAI LLMs.
Qualifications
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. 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: $199,400 - $265,800
Zone B: $179,400 - $239,200
Zone C: $165,500 - $220,600
This role may also be eligible for benefits, bonuses, commissions, and equity.
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.
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.
Tags: AIOps API Development APIs Architecture AWS Azure Databricks Deep Learning Distributed Systems Generative AI Generative modeling Java Jira Keras Kinesis LLMs Machine Learning Microservices MLFlow ML models MLOps NLP NumPy OpenAI Pandas Pinecone Pipelines Python PyTorch SageMaker Security TensorFlow Unsupervised Learning
Perks/benefits: Career development Competitive pay Equity / stock options Health care Salary bonus
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