Senior Associate, Machine Learning Engineer

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees.

We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development.

You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation.

At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses.

The Role:

As a Senior Associate, 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.

We are specifically seeking someone with deep domain knowledge in insurance, particularly in the investing and asset management areas. You'll apply this expertise alongside your ML engineering skills to build end-to-end solutions that transform how insurance companies manage investments, assess risk, and optimize portfolios.

What you'll do:

• Contribute to the development and deployment of ML models and pipelines specifically focused on insurance investment analytics, portfolio optimization, and risk modeling.
• Support production 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.
• Develop full-stack applications that operationalize ML models for insurance investment platforms, building both model APIs and user-facing interfaces.
• Apply insurance domain expertise to create solutions for investment portfolio management, asset allocation, and risk assessment.
• Build responsive web applications using modern frontend frameworks and RESTful APIs.

• 3 years of experience building and deploying ML models in production environments, including hands-on experience with model monitoring and diagnostics.
• Demonstrated domain knowledge in insurance, particularly in investment management, asset allocation, or insurance company portfolio management.
• Solid understanding of machine learning fundamentals, statistical methods, and data science workflows.
• Experience with multimodal, generative AI, or large language models (e.g., LLMs, diffusion models) is a strong plus.
• Exposure to model lifecycle management tools (e.g., MLflow, Weights & Biases) and production monitoring systems (e.g., Prometheus, Grafana).
• Proficiency in Python and familiarity with core ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
• Experience with data manipulation and analysis using tools like pandas, NumPy, and SQL.
• Familiarity with data visualization tools (e.g., matplotlib, seaborn, Plotly) to support storytelling and analysis.
• Excellent problem-solving skills, eagerness to learn, and comfort operating in fast-paced, evolving environments.
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Strong written and verbal communication skills, with the ability to clearly explain technical concepts and results to diverse audiences.

Preferred experience:

• Hands-on experience with Palantir platforms (e.g., Foundry, AIP, Ontology) - including developing, deploying, and integrating machine learning solutions within Palantir's data and AI ecosystem.
• Experience building production ML systems specifically for insurance use cases.

Position Location 

This position is based out of our Santa Monica, CA office. Consideration for a different working location will be considered on a case-by-case basis.  

Compensation

The base pay for this position is $170,000-190,000. A bonus will be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits. 

TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.