Position Title: Senior Machine Learning Engineer
Location: Melbourne, Australia
Job Type: Full-Time
Who We Are?
Tricentis is a global leader in continuous testing and quality engineering. The Tricentis AI-based, continuous testing portfolio of products provides a new and fundamentally different way to perform software testing. An approach that’s totally automated, codeless, and intelligently driven by AI. It addresses both agile development and complex enterprise apps, enabling enterprises to accelerate their digital transformation by dramatically increasing software release speed, reducing costs, and improving software quality.
Widely credited for reinventing software testing for DevOps, cloud, and enterprise applications, Tricentis has been recognized as a leader by all major industry analysts, including Forrester, Gartner, and IDC. We empower innovators to push the boundaries of software testing, fostering a global community of continuous learners who pioneer AI-powered, highly performant, highly secure end-to-end testing tools that accelerate our customers’ time to market including the largest brands in the world.
Role Overview:
As a Senior Machine Learning Engineer, you will contribute to the development, deployment, and optimization of machine learning and AI-driven solutions for our organization. This mid-level role is ideal for someone with a strong foundation in machine learning, generative AI, and software engineering, who is eager to grow their expertise by working on cutting-edge projects. You will collaborate with data scientists, software engineers, and product teams to deliver scalable, impactful AI solutions that drive business value.
Key Responsibilities:
Technical Development:
- Design and implement machine learning models and pipelines, focusing on scalability, robustness, and performance.
- Develop, train, and fine-tune models using generative AI, deep learning, and statistical techniques.
- Integrate machine learning models into production environments, ensuring reliability and security.
- Optimize ML systems for efficiency in real-time and batch processing workflows.
Collaboration & Communication:
- Work with data scientists to transition research prototypes into production-ready solutions.
- Partner with software engineers to ensure seamless deployment of ML models into existing systems.
- Collaborate with product managers to understand business needs and define technical requirements.
- Communicate technical findings and recommendations to stakeholders in a clear and accessible manner.
Continuous Improvement:
- Explore and implement new tools, frameworks, and techniques to enhance the efficiency of ML workflows.
- Identify opportunities to automate processes and improve decision-making through AI/ML solutions.
- Stay updated with advancements in AI/ML technologies and incorporate them into ongoing projects.
Required Skills & Qualifications:
Educational Background:
- Bachelor's or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
Technical Expertise:
- Solid understanding of machine learning concepts, including supervised and unsupervised learning.
- Proficiency in Python or similar programming languages, with experience in coding and debugging.
- Familiarity with ML frameworks and libraries like TensorFlow, PyTorch, or scikit-learn.
- Basic knowledge of cloud platforms (AWS, Azure, or GCP) and MLOps best practices.
- Basic knowledge of LangChain, LangGraph, or similar frameworks for building modular AI systems.
- Basic knowledge of generative AI models (e.g., GPT, DALL-E) or similar frameworks.
Production Experience:
- Experience in deploying ML models into production environments.
- Understanding of software engineering best practices, including version control, CI/CD, and testing.
- Familiarity with data pipelines and data management techniques.
Soft Skills:
- Strong problem-solving skills with a focus on practical, scalable solutions.
- Effective communication skills to collaborate across teams and explain technical concepts.
- Proactive and eager to learn new technologies and improve existing processes.
Preferred Qualifications:
- Experience in natural language processing, computer vision, or reinforcement learning.
- Familiarity with Agile development methodologies and tools like Jira or Confluence.
This position is an excellent opportunity to grow as a Machine Learning Engineer while working on innovative AI solutions. If you are passionate about technology and ready to tackle exciting challenges, we encourage you to apply!
Why Tricentis?
Tricentis Core Values:
At Tricentis, we strive for success while inspiring those around us by knowing what we need to achieve and how we’ll achieve it. Our core values serve as our guiding light to drive our every action and define our ways of working so that we can create and enjoy a successful journey and reach higher heights together.
- Demonstrate Self-Awareness: Own your strengths and limitations.
- Finish What We Start: Do what we say we are going to do.
- Move Fast: Create momentum and efficiency.
- Run Towards Change: Challenge the status quo.
- Serve Our Customers & Communities: Create a positive experience with each interaction.
- Solve Problems Together: We win or lose as one team.
- Think Big & Believe: Set extraordinary goals and believe you can achieve them.
We offer:
- Market conform salary and performance bonus
- Hybrid work arrangement (3 days return to office)
- Favorable working atmosphere in a rapidly expanding company
- Personal and professional development
- Permanent, full-time employment
Tricentis is proud to be an equal opportunity workplace. Qualified applicants will receive consideration for employment without regard to race, colour, ethnicity, gender, religious affiliation, age, sexual orientation, socioeconomic status, or physical and mental disability and other statuses protected by law.
