Senior Machine Learning Engineer

At Broadridge, we've built a culture where the highest goal is to empower others to accomplish more. If you’re passionate about developing your career, while helping others along the way, come join the Broadridge team.

We are excited to announce an opportunity for a Machine Learning Engineer to join our organization as part of our AI Enablement Team. In this role, you will play a crucial role in developing and enhancing our AI capabilities across the organization, with a specific focus on GenAI projects.

As a Machine Learning Engineer, you will be at the forefront of driving innovation and delivering cutting-edge solutions. Your expertise in machine learning and AI will contribute to the development of our platform, shaping its capabilities and providing impactful solutions.

Join our dynamic team and be part of a collaborative environment that fosters continuous learning and creativity. If you are passionate about machine learning, AI, and want to contribute to the platform capability development for our whole organization, we invite you to apply for the position of Machine Learning Engineer in our AI Enablement Team.

Job Responsibilities

• ML-Infrastructure on AWS: Support building a first-class machine learning platform that helps manage the entire model lifecycle: feature engineering, model training/evaluation, versioning, deployment/online serving, and monitoring prediction quality.
• Data Pipeline & Dataops: Design & develop libraries to help develop standardized data & model pipelines and frameworks that help standardize & scale the development teams.
• Model training with batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Reinforcement Learning, Decision Trees, Logistic Regression, Bayesian Analysis, Neural Networks, and others to develop and evaluate algorithms to improve product/system performance, quality, and accuracy.
• Experience in analyzing data quality, model quality, bias, explainability & perform required actions to improve model accuracy in production.
• Analyse & suggest efficient model retraining strategies, define validation strategy, training models & hyperparameters, verify data quality, model quality, lineage, etc.
• Stay up to date with state-of-the-art algorithms, repositories, and tools in Generative AI space (LLMs) e.g., Finetuning, quantization, pruning, etc. to help minimize training & inference requirements for models.
• Design and implement effective LLM tooling, and finetuning strategies.
• Staying up with the latest AI development, accordingly suggesting improvements to our roadmap and approaches, and disseminating learnings to colleagues.
• Help establish standards and best practices around Machine Learning – training and testing framework, coding standards, and engineering practices.

Qualifications & Skills

• Demonstrate a good understanding of natural language processing methods, including deep learning techniques, knowledge distillation, prompt engineering, and fine-tuning.
• 5-8 years of Industry experience with a minimum of 2 years of experience working in AWS & AWS Sagemaker and developing Sagemaker pipelines.
• Exhibit proficient skills in Python, and software engineering, along with expertise in deep learning frameworks (ML/distributed ML frameworks like TensorFlow, etc).
• Possess good communication skills and the ability to collaborate effectively with interdisciplinary teams.
• Experience in working with cross-functional teams of Engineers, Architects, DevOps but also UX, and Product designers.
• Proficient coding skills and strong software development experience (we use Spark, Python, and Java).
• Higher Education Degree in Computer Science/Statistics or a related field.

Hybrid Flexible at Broadridge
We are made up of high-performing teams that meet in person to learn and collaborate as needed. This role is considered hybrid, which means you’ll be assigned to a Broadridge office and given the flexibility to work remotely.

Broadridge associates helped us envision our Connected Workplace, a work model that allows associates around the globe to take advantage of the benefits of both on-site and off-site work to support our clients, one another, and the communities where we live and work. Our Connected Workplace is grounded in the concept of FACS: Flexible, Accountable, Connected, and Supported, which is our commitment to our associates. FACS supports our strong culture and allows us to achieve business goals while supporting meaningful work-life integration for our associates.

We are dedicated to fostering a diverse, equitable, and inclusive environment and committed to providing a workplace that empowers associates to be authentic and bring their best to work. We believe that associates can only do their best when they feel safe, understood, and valued, and we work diligently and collaboratively to ensure Broadridge is a company—and ultimately a community—that recognizes and celebrates diversity in all its dimensions.