Top Machine Learning Jobs

Owner of product features for Card Intelligence ML initiatives; collaborate with data scientists, engineers, and stakeholders to define roadmaps, break down epics into MVPs, prioritize features, and accelerate model-to-market delivery for fraud prevention.

Research and develop AI/ML models for systematic trading across FX, rates, commodities, and credit. Responsibilities include data featurization, model architecture and training, integrating models into production strategies, contributing to ML libraries and production algo systems, and owning P&L-impacting deployments.

Design and implement AI systems and scalable machine learning models, perform data wrangling and software engineering to deploy AI solutions, interpret data for client recommendations, collaborate across teams, uphold technical standards, and build client relationships while navigating complex, ambiguous problems.

The Staff Machine Learning Engineer will design, build, and optimize machine learning models and scalable data pipelines while collaborating with cross-functional teams to enhance Micron's products using AI/ML techniques.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Lead quantitative model risk assessments and develop alternative modeling approaches for loan loss forecasting and ACL. Apply econometric, statistical, and machine learning methods, maintain model accuracy, produce transparent documentation, and communicate technical results to management, regulators, and stakeholders. Leverage cloud and open-source tools, collaborate with model development and risk teams, and drive continuous improvement in modeling practices.

Lead development and enhancement of deposit and balance-sheet behavior models, including econometric time-series models. Collaborate with quantitative analysts and business partners to apply quantitative methods, validate and back-test models, communicate results to stakeholders and regulators, and maintain high-quality documentation and model governance.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead strategy and execution of ML-powered personalization and next-best-action across channels; define product vision, roadmaps, and KPIs; partner with data science and ML engineering to design, evaluate, deploy, and monitor LLM/ML solutions; own operating-memory/context data products, API-first cloud delivery, experimentation, and mentor product teams while ensuring privacy and fairness.

The role involves building customer valuation models, enhancing marketing efficiency via intelligent targeting, and implementing machine learning solutions for the Retail Bank.

Lead Gusto's AI/ML strategy, managing teams in Machine Learning Engineering, AI, and Risk Data Science. Ensure systems are reliable and impactful while fostering a culture of technical excellence.

Lead design and implementation of complex embedded and application software for signal processing and algorithm development (including machine learning) for EO/IR and electronic warfare systems. Provide technical leadership, mentor teams, produce design/project documentation, evaluate and optimize algorithms (C++), and collaborate with systems, hardware, and test engineers through full lifecycle development and customer technical reviews.

Lead end-to-end machine learning projects to improve customer engagement and retention. Build, test, and deploy models for user forecasting, personalization, and Casino engagement. Partner cross-functionally to scale solutions, mentor junior data scientists, and communicate model impact to influence product and marketing strategy.

Intern will own and deliver a scoped engineering project on Deepgram's voice platform (ASR/TTS/LLM/API/SDK), ship reviewed code to staging/production, use AI in development workflows, improve a component measurably, and present results with documentation.

Build and own fraud metrics, dashboards, and reporting. Design and implement real-time monitoring, alerts, and predictive ML-driven risk controls. Balance loss savings with customer friction, run experiments (A/B tests), partner with GTM teams, summarize findings to stakeholders, and assist teams with fraud triage.

Lead and mentor an agile engineering team to design, build, test, and operate secure, cloud-native production software. Provide technical direction, deliver high-quality code, drive product design decisions, and advocate firmwide engineering practices while applying AI/ML expertise.

Develop, evaluate, and deploy machine learning models for real trading environments; apply rigorous statistical techniques to measure performance, control overfitting, and assess model risk and interpretability; collaborate with traders and developers; maintain best practices and production-ready systems.

Lead and direct multidisciplinary teams to research, develop, test, integrate, and demonstrate advanced signal processing, optimization, and machine learning algorithms for radar, electronic warfare, and sensor systems. Oversee modeling/simulation, algorithm T&E, customer engagement, and technical briefings for defense and intelligence applications.

Lead and grow a machine learning team to build predictive models and ML features that drive revenue, retention, and product decisions. Partner with product and engineering, conduct exploratory analysis, design experiments, mentor engineers, and communicate insights to stakeholders.

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.

The role involves developing LLM applications for automated silicon design, optimizing models, curating datasets, and collaborating with other experts to integrate LLMs into EDA workflows.

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.

Design, train, evaluate, and productionize machine learning models (including embeddings and foundation models) on large-scale data. Partner with product and engineering to run experiments, improve customer experiences, and deploy scalable solutions using Spark and AWS.

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.