Senior Machine Learning Engineer - AI Solutions

At TWG Group Holdings, LLC (‘TWG Global’), we are at the cutting edge of innovation and business transformation, leveraging data and AI to manage a diverse portfolio that spans Investments, Securities, Insurance, Finance, Corporate Lending, Merchant Banking, as well as Sports, Media, and Entertainment. Data is one of our most valuable assets, and our commitment to AI allows us to transform that data into a powerful competitive advantage. We are pioneering a range of data and AI services that provide real-time intelligence to both our customers and workforce, enabling them to make informed decisions within interactive, cloud-native business applications. 

As we evolve into an AI-first, model-driven, and cloud-native company, we prioritize responsible data and AI practices that protect our customers and workforce while ensuring compliance within a regulated environment. Our goal is to lead by example, acting with the highest standards of ethics, responsibility, and transparency. This commitment drives our development of cutting-edge AI/ML business applications across our diverse product and service offerings. 

In this role, you will be at the heart of our data and analytics transformation, collaborating closely with management teams to achieve our strategic objectives and operational excellence. Our decentralized structure empowers each business unit to operate autonomously while benefiting from the strategic guidance and support of our central AI Solutions Group. 

Through our pioneering partnerships with major data and AI vendors, you will have the opportunity to work on transformative projects that will revolutionize marketing, distribution, customer acquisition, and internal processes. These initiatives are designed to enhance productivity, reduce costs, and create high-demand products and services. The advanced data systems we develop will grant management unparalleled access to real-time performance data, enabling swift, informed decision-making and agile business adjustments. 

Moreover, you will play a crucial role in leveraging our strategic relationships and equity positions in leading tech startups. These collaborations are not just about staying ahead of the competition—they are about creating true competitive advantages across our businesses. You will contribute to projects that are reshaping industries, from harnessing cloud-based supercomputing capabilities to driving key initiatives with major universities that are shaping the future of technology. 

At TWG Global, your work will directly contribute to our ambitious goal of generating sustained growth and superior returns, with expected annual equity returns exceeding 20%, including growing dividends. Join us as we push the boundaries of technology and innovation, delivering significant value across our portfolio while making a profound impact on the industries we serve. 

As a Senior Machine Learning Engineer, you’ll work alongside seasoned ML engineers and data scientists to design, build, and deploy machine learning systems that drive real business value. Reporting to the Executive Director of AI Science, you’ll gain hands-on experience contributing to production-ready AI applications, including predictive modeling, optimization, and monitoring tools used across the enterprise. 

This is a high-growth opportunity for someone with early industry experience (or strong academic grounding) in machine learning, eager to deepen their technical expertise and grow within a dynamic AI team building at the frontier of applied ML. 

Responsibilities: 

• Contribute to the development and deployment of ML models and pipelines across business-critical domains such as financial services and insurance. 
• Support productionization efforts, including model packaging, integration, deployment, and monitoring for model performance, drift, and reliability. 
• Conduct exploratory data analysis and feature engineering to support experimentation, prototyping, and model improvements. 
• Collaborate with senior engineers and data scientists to refine models and improve scalability, robustness, and accuracy. 
• Participate in building internal tools and infrastructure that enhance model training, testing, and monitoring workflows. 
• Clean, transform, and prepare datasets from diverse sources, ensuring data quality and consistency across ML pipelines. 
• Translate findings into clear, actionable insights, and communicate results effectively to technical and non-technical stakeholders. 

Requirements

• 3+ years of experience building and deploying ML models in production environments, including hands-on experience with model monitoring and diagnostics. 
• Solid understanding of machine learning fundamentals, statistical methods, and data science workflows. 
• Experience with multimodal,