Machine Learning Engineer Cognizant Technology Solutions CorpMachine Learning EngineerNew York, NY$110,000–$135,000 / yearYou will be a valued member of the AI and Data Engineering team and work collaboratively with Data Scientists, Data Engineers, Data Analysts, DevSecOps professionals, Product teams, and business stakeholders to deliver scalable, production-ready AI capabilities that create measurable business value. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world.
Machine Learning Engineer, Level 4 SnapchatMachine Learning Engineer, Level 4New York, NY$173,000–$259,000 / yearThe Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services. 3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field.
Agentic AI Machine Learning Architect - Senior Principal Slalom IncAgentic AI Machine Learning Architect - Senior PrincipalNew York, NY$215,000–$275,000 / yearDefine secure, scalable, cloud-native and hybrid reference architectures across AWS, Azure, and Google Cloud, including modern AI platform services such as Amazon Bedrock, Azure AI Foundry, Google Vertex AI, and enterprise data platforms. Experience defining agentic AI architecture patterns, including single-agent and multi-agent workflows, supervisor/worker patterns, state and memory management, workflow orchestration, human approval gates, and safe action execution.
Principal Applied Machine Learning Scientist Omada Health IncPrincipal Applied Machine Learning ScientistNY$270,480–$338,100 / yearLead research and development of individual- and population-level health trajectory models that predict future member states, risks, and likely progression paths using messy, real-world longitudinal healthcare data. Below is a summary of salary ranges for this role in the following geographies: California, New York State and Washington State Base Compensation Ranges: $270,480 - $338,100 , Colorado Base Compensation Ranges: $258,720 - $323,400 .
Data Science Machine Learning Internship (Summer 2027) Castleton Commodities International LLCData Science Machine Learning Internship (Summer 2027)Stamford, CTWork closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices.
Machine Learning Engineer, Generative ML, Level 4 SnapchatMachine Learning Engineer, Generative ML, Level 4New York, NY$173,000–$259,000 / yearOur team creates intuitive tools, platforms, and agentic systems that empower creators, developers, and internal teams to bring ideas to life, while advancing personalized, human-centric experiences across mobile, web, and wearable devices like Spectacles. The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
AI & Machine Learning Director AlixPartners LLPAI & Machine Learning DirectorNYRemote$170,000–$400,000 / yearIn this challenging role, you will be responsible for leading projects and client engagements, analyzing corporate performance, driving cost reductions, revenue growth and profitability improvement in your industry or functional area(s) of expertise in 'high stakes' situations. In this role, you will have the chance to create ETL workflows, scripts, statistical models, and visualizations while taking responsibility for the design, build, test, execution, and support of the data migration, cleansing, wrangling, etc.
AI & Machine Learning Senior Vice President AlixPartners LLPAI & Machine Learning Senior Vice PresidentNY$160,000–$310,000 / yearIn this challenging role, you will be responsible for leading projects and client engagements, analyzing corporate performance, driving cost reductions, revenue growth and profitability improvement in your industry or functional area(s) of expertise in 'high stakes' situations. At AlixPartners, we solve the most complex and critical challenges by moving quickly from analysis to action when it really matters; creating value that has a lasting impact on companies, their people, and the communities they serve.
Machine Learning, Assistant Vice President Morgan StanleyMachine Learning, Assistant Vice PresidentNew York, New YorkThe Machine Learning team in the Wealth Management (WM) Strategy & Analytics division at Morgan Stanley works on a breadth of applied AI research areas including but not limited to recommender systems, client personalization, graphical neural networks (GNNs), and natural language understanding/LLMs. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries.
Machine Learning Engineer Rapinno TechMachine Learning EngineerJersey City, New JerseyExperience working on various steps of developing a data science solution, like problem scoping, data gathering, EDA, modelling, insights, visualizations, monitoring and maintenance. Experience working with demand forecasting, supply chain optimization, driver analysis, time series analysis, statistical models, regression models and deep learning models.
NewStaff Machine Learning Engineer - Music Mission Spotify Technology SAStaff Machine Learning Engineer - Music MissionNew York, NY$227,495–$324,993 / yearAs a Staff Machine Learning Engineer, you'll help shape the Machine Learning technical strategy for this high-impact area, partnering across engineering, product, data science, research, and design to create tools that help artists grow their audiences while supporting Spotify's core business. You enjoy leading technically complex projects from idea through production and working closely with teammates and partners to deliver meaningful outcomes.
Machine Learning Engineering Manager, Personalization Spotify Technology SAMachine Learning Engineering Manager, PersonalizationNew York, NY$184,049–$262,928 / yearAs the Engineering Manager, you'll lead a talented team of machine learning, backend and data engineers while providing both technical direction and people leadership, helping the team deliver innovative ML capabilities that reach millions of listeners every day. The team is focused on training and improving the machine learning models that rank and personalize some of Spotify's most-loved listening experiences, including Radio and Daily Mix.
Staff Machine Learning Engineer, Personalization Spotify Technology SAStaff Machine Learning Engineer, PersonalizationNew York, NY$227,495–$324,993 / yearThis role is ideal for someone who enjoys taking models from research to production, driving technical direction in ambiguous problem spaces, and solving complex personalization challenges at global scale. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it.
Lead Machine Learning Engineer Capital One Financial CorpLead Machine Learning EngineerNew York, NY$197,300–$225,100 / yearIn this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
Senior Machine Learning Engineer AvePoint IncSenior Machine Learning EngineerJersey City, NJ$190,000–$220,000 / yearAvePoint's global channel partner program includes approximately 5,000 managed service providers, value-added resellers, and systems integrators, with our solutions available in more than 100 cloud marketplaces. Serve as a steward of adoption by partnering with product, engineering, and go-to-market teams to ensure solutions are usable, measurable, and successfully adopted by end users and customers.
Machine Learning Scientist, Algorithmic Recommendations (Email Targeting) New York Times CompanyMachine Learning Scientist, Algorithmic Recommendations (Email Targeting)New York, NY$121,000–$131,000 / yearThe annual base pay range for this role is between: $121,000—$131,000 USD For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. You will communicate complex ideas in machine learning while collaborating with all kinds of colleagues in in engineering, analytics, product management, marketing, editorial, and executive leadership groups.
Machine Learning Scientist, Algorithmic Recommendations Email Targeting The New York Times CoMachine Learning Scientist, Algorithmic Recommendations Email TargetingNew York, NY$121,000–$131,000 / yearYou will communicate complex ideas in machine learning while collaborating with all kinds of colleagues in in engineering, analytics, product management, marketing, editorial, and executive leadership groups. Basic Qualifications: PhD, MS + 2 years experience, or 3+ years experience in statistics, computational social science, applied mathematics, economics, or another quantitative/computational discipline.
Staff Machine Learning Infrastructure Engineer, Embedding Platform Reddit IncStaff Machine Learning Infrastructure Engineer, Embedding PlatformNYRemote$253,300–$354,600 / yearAs a Staff Machine Learning Infrastructure Engineer, you will own the technical direction for large-scale machine learning platform, guiding the development of advanced deep learning architectures and high-impact ML systems. You will partner with leadership to define ML roadmaps, drive innovation in scalable model design and training approaches, and ensure efficient, reliable deployment of ML models in production.
VP, Data Science / Machine Learning Lead - Capital Markets & Fixed Income TWG Global AIVP, Data Science / Machine Learning Lead - Capital Markets & Fixed IncomeNew York, NY$290,000–$300,000 / yearAt TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a range of industries, including financial services (particularly capital markets and fixed income), insurance, technology, media, and sports, by leveraging data and AI as core assets. 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.
NewTranslational Scientist, Applied Machine Learning and Agentic AI, Pharma R&D Tempus AITranslational Scientist, Applied Machine Learning and Agentic AI, Pharma R&DNew York City, New YorkYou will apply advanced scientific methodologies to develop new predictive models and utilize causal inference frameworks to analyze vast multimodal oncology data, helping to scale scientific discovery from a manual process to a high-throughput, automated engine. The Translational Scientist, Applied Machine Learning and Agentic AI will contribute to the technical development of cutting-edge agentic frameworks designed to automate the discovery of novel prognostic and predictive models in oncology.