Talantix.io
Atlassian•10.03.26
AI SCORE 8.5

Machine Learning Software Engineer - Remote

$120K–$150K/year
RemoteAI Software Development
Machine Learning•Java•Kotlin•Go•Python•AWS•GCP•Kubernetes•CI/CD•MLOps

About the Role

We are looking for a Machine Learning Software Engineer to join our team at Atlassian, where you will play a pivotal role in shaping the future of AI and ML across our products. This Machine Learning Software Engineer remote position offers an opportunity to work on cutting-edge technology that impacts teams globally.

What You'll Do

  • Design, build, and operate large-scale backend and infrastructure services for ML training and inference.
  • Collaborate with your teammates to solve complex problems, from technical design to launch.
  • Deliver cutting-edge solutions that are used by other Atlassian teams and products to build AI features that reach millions of customers.
  • Own services end-to-end – from design, implementation, infrastructure-as-code, CI/CD, through observability, on-call, and incident response.
  • Utilize your software development expertise to tackle infrastructure and architecture challenges.

Requirements

  • 4+ years of experience building and operating large-scale backend, infrastructure, or ML systems in a cloud environment.
  • Strong programming skills in at least one of: Java/Kotlin, Go, or Python.
  • Experience supporting or building systems for training, deployment, and serving of ML/LLM models (online or batch).
  • Strong experience designing and implementing distributed, fault-tolerant, high-throughput services, ideally for ML or data/compute platforms.
  • Hands-on experience with AWS and/or GCP, including networking, security, and compute services (EC2/GKE/EKS, GPUs, autoscaling, load balancing).
  • Experience automating deployment and operations of ML workloads – CI/CD, config and secret management, rollout/rollback strategies, monitoring and alerting.

Nice to Have

  • Practical experience building and running services or control planes on Kubernetes (deployments, operators/controllers, scaling, observability).

What We Offer

  • Competitive salary and benefits package.
  • Flexible remote work environment.
  • Opportunities for professional development and growth.
  • Work with a talented team passionate about innovation.
  • Be part of a company that values teamwork and collaboration.
Language Requirements
EnglishC1
BasicIntermediateAdvancedNative
Why This Job8.5 of 10

This Machine Learning Software Engineer role at Atlassian offers a unique opportunity to work remotely on innovative AI projects with a competitive salary and a focus on professional growth.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

→

Proficient in programming languages such as Python and Java, with hands-on experience in building and deploying machine learning models using AWS or GCP, ensuring familiarity with MLOps practices.

→

Adaptable in a remote work environment, demonstrating self-motivation to manage time effectively while collaborating across time zones and maintaining productivity in a distributed team.

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Experience with CI/CD pipelines and container orchestration using Kubernetes, coupled with a problem-solving mindset that embraces experimentation and iteration in developing scalable ML solutions.

Learning Resources

→Machine Learning with Python: From Linear Models to Deep Learningcourse
→AWS Machine Learning Documentationguide
→Kubernetes Official Documentationarticle

Career Path

Machine Learning Software Engineer - Remote(Now)→Senior Machine Learning Engineer(1-2 years)→Machine Learning Architect(3-5 years)

Market Overview

Market Size 2024
$20.6B
Annual Growth
38.8%
AI Adoption
83%
Investment
+150%
Labour Demand
+45%
Avg Salary
$130K

Skills & Requirements

Required
Machine LearningJavaKotlin
Growing in Demand
Deep LearningNatural Language Processing (NLP)Data Engineering
Declining
R (as a primary language)Matlab

Domain Trends

Increased Focus on MLOps
Organizations are adopting MLOps practices to streamline the deployment and management of machine learning models, with a 50% increase in companies implementing these practices in 2024.
Integration of AI with Cloud Services
There is a growing trend of integrating AI capabilities with cloud platforms, with 70% of enterprises leveraging AWS or GCP for machine learning workloads, highlighting the importance of cloud proficiency.
Rise of Automated Machine Learning (AutoML)
The AutoML market is projected to grow by 25% annually, allowing non-experts to build machine learning models, which emphasizes the need for ML engineers to focus on more complex tasks and model optimization.

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