We are seeking a highly skilled Senior Machine Learning Engineer to join our team in advancing the frontier of AI-driven solutions. In this role, you will play a critical part in designing, implementing, and maintaining both traditional machine learning models and cutting-edge systems built with Generative AI technology. The ideal candidate will have extensive experience in GenAI, AWS services, machine learning model development and deployment processes, and data engineering tools. You will be responsible for implementing GenAI applications, evaluating models, and ensuring their performance and governance, all while aligning solutions with our business objectives.

Key Responsibilities:

• Develop, implement, and maintain robust machine learning models using GenAI.

• Engage in prompt engineering to optimize the interaction with large language models, with other AI systems or tools.

• Utilize techniques like Retrieval-Augmented Generation (RAG) to enhance AI solutions with real-time information retrieval.

• Develop and design graph databases using tools such as NetworkX or AWS Neptune for relationship-oriented data modeling.

• Fine-tune Large Language Models (LLMs) to tailor solutions to specific business needs and improve model efficiency.

• Leverage AWS services (including S3, ECS, ECR, Lambda, SageMaker, and more) to build scalable machine learning solutions.

• Utilize data engineering skills with Glue and PySpark for efficient data preparation and processing.

• Conduct model evaluation and testing to ensure accuracy, reliability, and robustness.

• Monitor machine learning models in production, implementing strategies for ongoing performance tracking and optimization.

• Ensure the security of models and data through secure API integration, utilizing tokens and comprehensive data security principles.

• Govern models in compliance with the Machine Learning Development Lifecycle (MDLC) and Machine Learning Production Lifecycle (MPLC) processes.

• Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders, to deliver impactful machine learning solutions.

• Stay up-to-date with the latest advancements in machine learning, generative AI technologies, and methodologies.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.

• 5+ years of experience in machine learning and data engineering roles.

• Experience with prompt engineering and fine-tuning large AI models.

• Familiarity with Retrieval-Augmented Generation (RAG) techniques.

• Proficiency in designing graph databases using tools like AWS Neptune, Neo4J or NetworkX.

• Proficiency in Python, with a strong understanding of libraries such as TensorFlow, PyTorch, and Scikit-learn.

• Extensive experience with AWS services relevant to machine learning, including SageMaker, Glue and PySpark.

• Experience with secure API integration and a solid understanding of data security practices.

• Strong understanding of data preprocessing, feature engineering, and model training/evaluation.

• Experience with model monitoring, performance analysis, and optimization techniques.

• Familiarity with model governance frameworks, including MDLC and MPLC processes.

• Excellent problem-solving skills, with the ability to innovate and think critically about complex issues.

• Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Preferred Qualifications:

• Experience with advanced AI models, such as large language models, reinforcement learning.

• Certifications in AWS Machine Learning or related areas is preferred.

Special Factors

Sponsorship

Vanguard is offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

Our commitment to diversity, equity, and inclusion

Vanguard’s commitment to diversity, equity, and inclusion (DEI) is central to our ability to deliver on our mission. We aspire to create a work environment that is inclusive, equitable, and diverse—one that enables our employees, whom we call crew, to thrive and bring their best selves to work every day on behalf of our clients.

Cultivating DEI lifts our entire organization, and everyone shares accountability for our progress—from our senior leaders who lay the foundation and set the example for inclusive behaviors to crew who are growing in their personal DEI learning experiences.

Together, we’re on a mission. We are fueled by the value of diverse voices and connected through friendships and a culture of care—for our clients, our communities, and each other.    

Vanguard’s DEI journey has no finish line. Our commitment is enduring, and we remain focused on the path ahead. To learn more about Vanguard goals and progress toward DEI, download our Diversity, Equity, and Inclusion Report.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.