Top Machine Learning Jobs

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.

Summer analyst will build and maintain quantitative models and algorithms for systematic trading and market-making, value and hedge transactions, conduct alpha research, calibrate models, optimize portfolios, and collaborate with traders, technologists, risk, and sales to deploy data-driven trading strategies.

Use ML, LLMs, and GenAI to detect and prevent card fraud by analyzing large transaction datasets, building automation and reporting, developing POCs, and delivering actionable recommendations to cross-functional partners to optimize risk and customer experience.

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.

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.

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.

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.

The analyst will leverage multi-INT data for curation and development of labeled data for Machine Learning, focusing on SAR imagery. Responsibilities include recommending curation strategies and addressing data gaps for diverse datasets.

Build, deploy, and monitor machine learning and pattern-recognition models to detect lending fraud. Analyze large transactional datasets with Python and SQL, partner with Fraud Operations to iterate on features and reduce false positives/negatives, communicate findings to stakeholders, apply AI in production, and mentor team members.

Build and validate ML and statistical models, perform exploratory and descriptive analyses, create visualizations, maintain data pipelines and quality, collaborate with clients to deliver tailored AI/ML solutions, mentor junior staff, and apply modern AI techniques including generative AI and NLP to solve business problems.