Top Hybrid Machine Learning Engineer Jobs

Lead design and delivery of low-latency market-making and automated trading strategies. Translate quantitative research into production systems, build backtesting and real-time decision engines, ensure scalability and observability, manage risk-aware optimization, and influence cross-functional teams on strategy and technical direction.

Partner with senior data scientists and engineers to explore large datasets, prototype and validate interpretable ML models, support deployment and monitoring, translate business requirements into analytics, build dashboards and visualizations, and adopt best practices for model development, testing, and productionization to support Corporate & Institutional Banking decisions.

The Principal Machine Learning Engineer will develop ML algorithms and optimize performance on ARM computing platforms, collaborating across hardware, software, and ML algorithms, while focusing on performance, power, and area.

Lead end-to-end machine learning solutions for autonomous driving, mentor engineers, design advanced models, and ensure safety and reliability in diverse scenarios.

Lead and develop advanced machine learning models for autonomous driving, collaborating with teams, and driving technical initiatives in a hybrid work environment.

As a Staff Research Scientist, you'll design advanced algorithms in machine learning, mentor others, and influence technical roadmaps for autonomous driving.

As a Sr. Distinguished Engineer at Capital One, you will lead AI/ML engineering teams, design and build ML applications, mentor engineers, and drive technology innovations in machine learning.

Manage a team to assess model risks, build and validate machine learning models while leveraging advanced technologies and cross-functional collaboration.

Senior individual contributor building and maintaining underwriting and credit decisioning ML systems for Cash App Borrow and Afterpay. Responsibilities include feature engineering, model training, calibration, experimentation, deployment, monitoring, and portfolio-level analysis. Collaborate with cross-functional teams to align models with business and regulatory goals and develop AI-native engineering workflows and governance for reliable, auditable model development.

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.

Lead development and deployment of predictive models, analytics, and dashboards to support Sales, Marketing, Customer Success, and GTM operations. Mentor data scientists, partner with business leaders to prioritize analytics, ensure data governance and quality, and present insights to executives. Work with Snowflake/data lakes, build scalable ML solutions, and drive analytics adoption across the enterprise.

The ERP AI Engineer - Manager at PwC leads teams in AI/ML engineering, manages client relationships, and designs AI solutions, all while mentoring team members and addressing complex business challenges.

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.