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. Atlassian is looking for a Machine Learning Engineer to join our Core Machine Learning team based in Mountain View, CA. The Core Machine Learning team builds and deploys ML modeling solutions to drive revenue generation, expand our active user base and provide sophisticated forecasting for company top-line metrics. This is accomplished by driving the complete end-to-end ML development cycle. This is a unique opportunity to work in a collaborative environment, implement the cutting edge machine learning techniques, especially recommendation systems, and tackle challenging and distinctive problems. Responsibilities Your future team The Core Machine Learning team sits within the Data Technology Insights group in the Atlassian Corporate Engineering Organization. We work cross-functionally across stakeholders in Growth, GTM, Product, Finance and Sales organizations, providing AIML applications. Our team consists of ML engineers and system engineers, and provides many opportunities for collaboration, knowledge sharing, and individual growth. We are highly nimble, with a focus on velocity between conceptualization and initial output, and laser-focused on business impact. What you’ll do As a Machine Learning Engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, collaborating with business, engineering, and analytics teams, to build large scaled recommendation system to recommend the best growth drivers and actions to our customers. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. Your role is pivotal, stretching beyond these tasks, ensuring AI/ML's transformative potential is realized across our offerings. Qualifications Your background On the first day, we'll expect you to have - Master or PhD in a quantitative subject (Mathematics, Computer Science, Statistics, Operations Research, or relevant work experience) - 3+ years of Experience in machine learning domain - Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks) - Experience building and scaling machine learning models in business applications using large amounts of data - Agile development mindset, appreciating the benefit of constant iteration and improvement It's great, but not required, if you have - Experience in developing recommendation algorithms and AI applications for Sales - Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space - Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions 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: $175,500 - $229,125 Zone B: $158,400 - $206,800 Zone C: $145,800 - $190,350 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.

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! . See yourself at Twilio Join the team as Twilio’s next Machine Learning Engineer. About the job This position is needed to drive innovation and the development of cutting-edge products that serve developers, builders, and operators within Twilio’s Data & Observability Substrate organization. This is a hands-on, builder-focused engineering role that bridges Product, Design, and Engineering to develop, evaluate, and maintain scalable, low-latency, ML-based systems for real-time applications. You will lead rapid research-to-production cycles that translate business ideas into solutions for complex problems—such as streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks—with the goal of delivering personalized customer experiences. You will collaborate closely with a cross-functional team of engineers, architects, product managers, UI/UX designers, and ML/data science partners to deliver robust, reliable solutions that power customer success. Responsibilities In this role, you’ll: - Partner with product, UX, and technical stakeholders to analyze business problems, clarify requirements, define scope, and translate them into measurable ML problem statements. - Design, implement, and maintain scalable, enterprise-grade ML solutions in production. - Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling. - Implement monitoring and evaluation frameworks to continuously improve data quality, model performance, latency, and cost through feedback loops. - Partner cross-functionally with Product, Data Science/ML, Engineering, and Security to deliver resilient, scalable, and compliant ML-powered services. - Demonstrate end-to-end systems understanding and articulate the “why” behind model and system design choices. - Own operational excellence: SLAs, on-call, incident response, customer feedback triage, and blameless post-mortems. - Drive engineering excellence via AI-assisted SDLC, code reviews, automated testing, MLOps best practices, knowledge-sharing, and mentoring. - Actively adopt AI-assisted practices to improve implementation and collaboration efficiency. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: - Strong foundation in ML/AI (statistics, probability, optimization) with the ability to apply these concepts to real-world problems. - 5+ years of experience building, deploying, and operating data and ML systems in production. - Proficient in Python, Java, and SQL; strong software engineering fundamentals (system design, testing, version control, code reviews). - Hands-on experience with workflow orchestration and data pipelines (e.g., Airflow, Kubeflow) and cloud data platforms/storage (e.g., SageMaker Feature Store, Snowflake, DynamoDB, OpenSearch). - Experience with the ML lifecycle and MLOps tooling (e.g., MLflow, Metaflow, SageMaker; LLM/agent frameworks such as LangChain/LangGraph; model evaluation/observability tools such as Galileo or similar). - Working knowledge of containerization and cloud infrastructure, including Docker and Kubernetes, GitOps/CI/CD tools (e.g., Argo CD), and at least one major cloud platform (AWS, GCP, or Azure). - Understanding of data modeling and scalable systems, including distributed computing and streaming frameworks (e.g., Spark/EMR, Flink, Kafka Streams); familiarity with GPU-based implementation is a plus. - Demonstrated ability to ramp up quickly and operate effectively in new application/business domains. - Strong written and verbal communication skills: able to document and present designs and decisions, and comfortable giving/receiving feedback in an Agile environment. Desired: - Familiarity with ML problem areas and techniques, including recommendation systems (e.g., graph-based approaches, two-tower models), time-series modeling (classical and deep learning), representation learning (e.g., embeddings), anomaly detection, and causal inference. - Practical experience with LLMs and generative AI workflows, including foundation model fine-tuning, RAG, and vector databases. - Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research. - Domain experience (plus) in communications, marketing automation, or customer engagement analytics. - Familiarity with AI-assisted development tools (e.g., Claude, GitHub Copilot/Codex, Cursor, etc.). - Advanced degree preferred (M.S. or Ph.D.) in a relevant field. Location This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Compensation *Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only. The estimated pay ranges for this role are as follows: - Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $155,520.00 - $194,400.00. - Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $164,640.00 - $205,800.00. - Based in the San Francisco Bay area, California: $182,960.00 - $228,700.00 - This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Application deadline information Applications for this role are intended to be accepted until April 20th, but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

• Frame open-ended, real-world problems into well defined ML problems • Make use of and improve on existing data acquisition and model training/evaluation pipelines to create appropriate datasets and obtain model feedback • Leverage cutting-edge research and technology to create custom solutions • Design and run experiments to test new ideas or improvements to existing models • Build visualization and monitoring tools to evaluate the quality of our data and models • Collaborate across teams and product to deliver solutions that fit within business and organizational requirements • Review code of other Machine Learning Engineers

• Design and optimise AI-ready tools and APIs that enable LLM platforms (ChatGPT, Claude, Gemini and others) to reliably interact with Canva's design capabilities — focusing on optimising tools to decrease latency and reduce costs without sacrificing end-user performance • Pioneer agent to agent communication • Build and maintain evaluation frameworks to systematically measure tool-use accuracy across platforms, including proxy-based fast evals for development velocity and real-client evals for production validation • Experiment with LLM orchestration and agent architectures — Develop Canva agents that any 3rd party provider can call to design quickly, efficiently and at scale • Automate entire workflows such as marketing campaigns by connecting user intent, Canva and third parties • Develop observability and monitoring systems to track how AI assistants consume Canva's tools in production, identifying failure patterns and driving continuous improvement • Work across platform boundaries — understanding the behavioural quirks of different LLM platforms and building adapters or configurations that account for them at scale • Collaborate with AI partners and internal teams to shape tool design, API evolution, and integration strategy aligned with Canva's broader AI ecosystem goals