Position Title: Machine Learning Engineering Lead Location: Melbourne Australia Job Type: Full-Time Role Overview: As the Machine Learning Engineering Lead, you will be responsible for leading the development, deployment, and scaling of machine learning and AI-driven solutions across our organization.
This role requires a deep understanding of generative AI (Gen AI), autonomous agents, deep learning, machine learning, and statistics, combined with hands-on experience in coding and productionizing ML-enabled applications.
You will work closely with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to deliver innovative and impactful AI solutions that drive business value.
Key Responsibilities: Leadership & Strategy: Lead the design, development, and deployment of machine learning models, with a focus on generative AI and autonomous agent capabilities.
Mentor and guide a team of machine learning engineers, fostering a culture of innovation, collaboration, and continuous improvement.
Stay up-to-date with the latest advancements in AI/ML technologies and apply them to solve complex business challenges.
Technical Development: Architect, design, and implement scalable ML systems and pipelines for real-time and batch processing, ensuring high availability, performance, and reliability.
Develop and productionize machine learning models, including deep learning, statistical models, and advanced algorithms, using best practices in software engineering.
Utilize generative AI techniques and autonomous agent frameworks to create intelligent systems capable of autonomous decision-making and task execution.
Ensure the integration of ML models into production environments, optimizing for scalability, robustness, and security.
Collaboration & Communication: Collaborate with data scientists to transform research prototypes into production-ready models, ensuring code quality and maintainability.
Work closely with product managers and stakeholders to define AI/ML use cases, requirements, and deliverables.
Communicate complex technical concepts to non-technical stakeholders, providing insights and recommendations based on data-driven analysis.
Innovation & Continuous Improvement: Lead the evaluation and implementation of new tools, frameworks, and technologies that enhance the efficiency and effectiveness of ML workflows.
Identify opportunities to leverage AI/ML to automate processes, improve decision-making, and enhance user experiences.
Promote a culture of experimentation, encouraging the team to explore new ideas and approaches to solving business problems.
Required Skills & Qualifications: Educational Background: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
A Ph. D.
is a plus. Technical Expertise: Strong proficiency in machine learning, deep learning, and statistical modeling, with a solid understanding of supervised and unsupervised learning techniques.
Experience with generative AI models, such as GPT, DALL-E, or similar, and autonomous agents capable of executing complex tasks.
Proficiency in programming languages such as Python or C#, with hands-on experience in coding, debugging, and optimizing ML algorithms.
Experience with ML frameworks and libraries, such as Tensor Flow, Py Torch, scikit-learn, Keras, or similar.
Solid understanding of cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices for deploying and managing ML models at scale.
Production Experience: Demonstrated experience in deploying and maintaining ML models in production environments, ensuring scalability, performance, and security.
Knowledge of software engineering best practices, including version control, CI/CD, testing, and code reviews.
Experience with data pipelines, ETL processes, and data management techniques to ensure high-quality input data for ML models.
Soft Skills: Strong problem-solving skills with the ability to think critically and creatively to solve complex technical challenges.
Excellent communication skills, with the ability to articulate technical concepts to a diverse audience.
Leadership and team management skills, with a track record of mentoring and developing junior engineers.
Preferred Qualifications: Experience with reinforcement learning, natural language processing, or computer vision.
Experience with Agile development methodologies and tools like Jira or Confluence.
We offer: Market competitive salary + success-oriented commission + superannuation Favourable working atmosphere in a rapidly expanding company Personal and professional development Permanently, full-time employment And more! 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.
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