Find Jobs
Find Jobs Near You – Available Work in Your Location
Skip to job details
TG
TWG Global AI
Senior Machine Learning Engineer - AWS, Real-Time Inference, Pipelines
Career Insights for Machine Learning Engineer
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on California data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$168,439 / year median in California
Job Description
Senior Machine Learning Engineer - AWS, Real-Time Inference, Pipelines TWG Global AI Santa Monica, CA Job Details Full-time $190,000 - $290,000 a year 5 hours ago Qualifications AI models Data storage Public Cloud Production systems Machine intelligence Machine learning (ML) fundamentals Real-time data processing implementation AI Python Full Job Description At TWG AI, 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, 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 ML Engineer for AWS and Real-Time Inference, you'll own the fast path: ingesting live trading data and scoring it in near real time. It's a systems-heavy role focused on streaming, low-latency inference, and the retraining cadence that keeps models current and most directly determines whether the systems keep up with live markets. What you'll do: Streaming and storage pipelines that feed both model training and low-latency inference. The online inference path and its latency. A real-time detector microservice is built and unit-tested but not yet deployed — it needs to be connected to a run-time model and hold latency under live load. One known, non-trivial problem lives here: batch scoring ranks across a whole population, but single-account (or single-wallet) real-time scoring has no population to rank against, so it must threshold on calibrated raw scores. The model retraining cadence as data and labels accumulate, including drift-triggered retraining. Productionizing new features and detectors on the fast path, in partnership with data science. Requirements Strong data / ML engineering experience with streaming systems (e.g., Kafka / Kinesis / MSK) and modern data storage formats Experience building low-latency, high-throughput inference services Proficiency in a systems language (e.g., Go) alongside Python Production AWS experience Familiarity with financial market data or trading protocols a plus — the US feed is a