Top Machine Learning Jobs

Perform data cleaning, exploratory analysis, and build/productionize ML and statistical models (including NLP) to generate business value for service and fluids-analysis domains. Collaborate with cross-functional teams, present findings to stakeholders, and work independently on analytics projects within an Agile environment.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Lead development and deployment of optimization and machine learning models to improve retail banking decisions. Translate business problems into mathematical formulations, build production-grade optimization and simulation models, collaborate with Product and Engineering to integrate solutions, and run end-to-end model development, evaluation, validation, and implementation.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

As a Principal Machine Learning Systems Engineer, you will lead the development and implementation of machine learning systems and solutions to enhance team collaboration and productivity across Atlassian's software products.

Develop and deploy econometric and machine learning models for credit risk, loss forecasting, CECL/allowance, stress testing, and capital allocation. Partner with business lines to build cloud-based analytical solutions, automate processes, communicate results to stakeholders, and own the full model lifecycle from data exploration through deployment and monitoring.

Develop, validate, and maintain RMBS prepayment and credit/default models; perform large-scale data processing and ML analysis; build analytics platforms and monitoring tools; support valuation, hedging, risk assessment, model review, and client/internal training.

Contribute to machine learning model design, training, and evaluation for fraud detection. Communicate findings, develop metrics, and support production ML workflows while ensuring compliance and model governance.

Lead the design, development, and deployment of advanced machine learning solutions at Optum Tech, mentoring junior engineers and collaborating across teams.

Design and maintain data pipelines and BI infrastructure, ensure data quality, optimize SQL and transformations, build and validate predictive and ML models, support deployment and BI integration, and collaborate with stakeholders to deliver scalable analytics solutions.

Lead product strategy and execution for signals exploitation and tracking capabilities. Define roadmaps, shape backlogs with customers and product owners, support architecture and design reviews, and drive development and demonstration of advanced algorithms and software for DoD and Intelligence Community missions. Balance reuse, integrated system offerings, and component supply-chain opportunities while leading engineering teams through the Agile lifecycle and supporting technical marketing and business development.

This internship focuses on researching low-latency ML inference and hardware acceleration, involving project ownership, collaboration with engineers, and presenting findings.

Partner with healthcare clients to discover, design, and deliver production-grade AI/LLM solutions. Architect cloud-native systems, build and deploy ML/LLM applications, prototype rapidly, troubleshoot distributed systems, and lead client engagements to drive measurable business outcomes while collaborating across product, platform, and engineering teams.

As a Staff Machine Learning Engineer, you'll enhance credit products through advanced modeling techniques, data analysis, and ML operations, supporting robust decision-making processes.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Lead modelling and analysis roadmap for FX products: forecast and monitor FX volatility, optimise trade execution with statistical/ML models, run customer and profitability analyses, and partner with product, trading, risk, and engineering to translate insights into trading and product decisions.

Develop and deploy machine learning systems for Mars missions, enhance atmospheric modeling, and integrate multi-modal data for autonomous science.

Responsible for validating payment network models, including fraud and AML. Engage with stakeholders, improve model accuracy, and leverage innovative technology for data analysis.

The role involves developing machine learning systems for Mars atmospheric modeling and multi-modal data fusion, contributing to autonomous science in space missions.

Build and validate statistical and machine learning models for credit card loss forecasting, modernization, and allowance (CCAR). Partner with data scientists, engineers, and product managers to transform data, automate insights, support model governance, and present model risk impacts to executives using cloud and big-data tools.

Technical lead for end-to-end ML and CV pipelines to reconstruct, validate, and maintain map primitives from multi-modal vehicle sensor data. Architect scalable offline and production map reconstruction systems, define technical strategy, drive cross-functional integration, mentor senior engineers, and ensure robustness, safety, and operational scalability for national-scale mapping.

Develop and deploy machine learning solutions for autonomous vehicles, mentoring engineers and collaborating on model implementations.

Lead and deliver advanced analytics and machine learning solutions to support pricing, revenue optimization, and partner relationships. Collaborate with cross-functional teams to design, validate, and implement models at scale using large transaction datasets and modern big-data tooling. Translate technical insights into actionable business recommendations.

Design, build, and deploy core ML systems and components for an AI agent platform, including search ranking, proactive suggestions, orchestration, routing, and planning; integrate cutting-edge LLMs and ensure high-quality user experiences while working autonomously in a fast-paced, collaborative environment.

Perform data analysis and test & evaluation of machine learning algorithms; develop algorithms for physical and autonomous systems; transition algorithms to software and embedded systems; work with stakeholders to present results and solutions; research new ML and data-analysis methods; handle large, multidimensional datasets and data pipelines.