Senior Ai Ml Data Model Architect Jobs

Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, in-person in the London office. Responsibilities: Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. Support deployment and monitoring of search and ranking models in a scalable and performant way. Help build and iterate on RAG pipelines for grounding and answer generation. Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment Experience with Rust will be a plus

Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, part-time, in-person in the Belgrade office. Responsibilities: Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. Support deployment and monitoring of search and ranking models in a scalable and performant way. Help build and iterate on RAG pipelines for grounding and answer generation. Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment Experience with Rust will be a plus What we're looking for: You’ve built something you’re proud of: Not just a class assignment - we want to see a project y

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior AI Engineer, Big Data & AI Solutions Overview The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard’s Safety Net product, the team develops and enhances models that analyze billions of transactions and identify suspicious activity. As a Senior AI Engineer, you will work at the intersection of big data engineering and AI/ML, helping build and support the data, features, models, and production processes behind fraud detection. Ideal Candidate Profile You are a big data and AI/ML engineer who has used Apache Spark in a professional environment and has hands-on experience working within CI/CD-driven engineering environments. You understand how large-scale data moves from raw inputs through data and feature pipelines into machine learning models, and how those models are deployed, monitored, and improved in production. Large-scale data → Spark/PySpark → Data & Feature Pipelines → ML models → Production Deployment→ CI/CD→Monitoring & Drift Detection → Optimization & Retraining Experience with Generative AI, RAG, LLMs, or agentic AI is valuable, but the foundation for this role is large-scale data engineering and production AI/M

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Product Data Science team is looking for a Full-stack Senior Data Scientist to come aboard and be part of Snowflake’s most critical initiatives. In this role, you will work closely with our Product and Engineering teams on everything from core operations, to innovative AI/ML tools, to our fastest-growing new and experimental features. You will work on long-running analytical initiatives yielding substantial product enhancements. This is a strategic, high-impact role that will help shape the future of Snowflake products and services. PLEASE NOTE: The position level is determined during the interview process and is influenced by various factors, including experience, educational attainment, skill level requirements, and overall interview performance. AS A SENIOR FULL STACK DATA SCIENTIST AT SNOWFLAKE YOU WILL: Be a proactive partner to Product Management and Engineering to shape feature roadmaps and help design metrics and analytical workflows to evaluate their success and effectiveness. Build efficient data models and high quality production pipelines and partner with Engineering for all necessary telemetry. Build scalable and extensible analytics/ML/causal inference frameworks to uncover feature usage patterns, subtle issues with the system, potential performance enhanc

ROLE SUMMARY As an AI-enabled strategic scientific leader, you will partner with Oncology Research Leadership to integrate AI-driven strategies that will drive data-informed decision-making across our Oncology Research pipeline. As the AI Portfolio Lead, you will bridge cutting-edge AI/advanced analytics with deep Oncology R&D expertise to guide our portfolio strategy. Working as an individual contributor reporting into the Head, Portfolio Strategy and Program Management, you will analyze and continuously assess Oncology Research projects using AI-driven insights (predictive models, scenario simulations, competitive intelligence) and propose actionable strategies to Oncology Research Leadership. This role is science-focused and spans across discovery and preclinical stage programs, ensuring that our project teams pursue the most promising scientific approaches and mechanisms of action. Your work will directly inform pipeline prioritization and resource allocation decisions, enhancing the quality and objectivity of governance deliberations with robust data. ROLE RESPONSIBILITIES Portfolio Analysis and Insights: Continuously analyze the oncology Research portfolio (ESD through Preclinical) using advanced AI/ML tools and analytics to evaluate each program’s scientific strength, probability of success, and strategic portfolio fit per disease area strategies. Strategy Recommendation: Develop and propose data-driven portfolio strategies (at both project and portfolio levels) to senior leaders and Research governance committee. Use scenario analysis and predictive modeling to highlight optimal project prioritization, pipeline balance, and resource allocation scenarios. AI-Enabled Decision Support: Integrate AI-derived insights (e.g. machine learning predictions, knowl

Senior AI Product Manager - Product & Experience Location: London (Hybrid) | Practice Area: Product & Experience | Type: Permanent Shape meaningful products that improve customer outcomes across financial services and energy. The Role As a Senior Product Manager within Capco’s Product & Experience practice, you will define, build, and scale AI-enabled products and experiences. You will translate emerging AI capabilities into real-world value, working closely with clients and cross-functional teams to deliver products that are commercially impactful, user-centric, and production-ready within complex, regulated environments. You will also operate as an AI-enabled Product Manager, leveraging modern AI tooling to accelerate discovery, decision-making, and delivery. What You’ll Do Lead product engagements across clients and Capco teams, embedding AI into both product strategy and delivery workflows Define and deliver AI-native product strategies, including value propositions, roadmaps, and commercialisation models Own products end-to-end, from discovery through delivery and iteration, incorporating rapid experimentation, prototyping, and AI-assisted development Identify, shape, and prioritise AI/GenAI/agentic/ML use cases, translating them into scalable product features and measurable business outcomes Partner closely with data science and engineering teams to bring ML models and AI systems into production, balancing performance, risk, and cost Champion responsible AI by embedding governance, explainability, and regulatory considerations into product design and lifecycle Mentor and lead multidisciplinary teams, fostering a culture of experimentation, learning, and AI & data fluency What We’re Looking For Experience in developing and delivering digital products/portfolios across B2B, B2C, or B2B2C contexts within financial services D

P-78 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the ML/AI Environments team you will build the system that enables the AI researchers and engineers to set up their desired training and serving environments. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. The impact you will have Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly. Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks platform. Examples include improving performance of setting up virtual environments for short training and data processing sessions, improving observability to help customers debug when runs fail, etc. Interact with turnkey customers and product managers to envision new features and identify areas for improvement. Shape how developers and data scientists build and interact with AI on Databricks. What we look for 5+ years of experience in backend or infrastructure engineering wi

REQ ID: CSQ128R7 Location: London, United Kingdom - Remote location for candidates to be based in the United Kingdom region ONLY ( not remote from any other country) Mission The Forward Deployed AI Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services (PS) engagements to help our customers build and productionize first-of-its-kind AI applications with a focus on GenAI. We work cross-functionally with AI/ML Product, Research, and Engineering to shape long-term strategic priorities and initiatives. We are looking for a world-class leader to lead and grow our UK AI FDE team. In this role, you will lead customers on their AI/ML transformation with Databricks, push the boundaries of our product, recruit and develop top data scientists/machine learning engineers, and manage a portfolio of key EMEA accounts. You will report directly to the Director AI FDE. The impact you will have: Lead and scale a world-class AI/ML professional services team, including hiring, mentoring, and building a team structure to support long-term growth and execution at scale Develop and expand executive relationships with EMEA customers and partners (including VP+, CIO/CDO-level stakeholders), acting as a trusted advisor during complex technical engagements and AI transformations Align with Field Engineering and Sales Leaders to define joint strategies for strategic accounts and ensure strong delivery coordination across functions Lead strategic AI PS initiatives, practice development, and standardised delivery processes; design scalable engagement models and reusable solutions for repeatability across the global team Shape cross-functional collaboration by influencing Product, R&D, and GTM—ensuring voice-of-customer insights and delivery learnings help inform the product roadmap and GTM strategy Own OKRs for AI-services led accounts, revenue, utilisation, and public references Represent Databricks as a thought le

AI Business Consultant / Senior Consultant Location: London (Hybrid) | Practice Area: Business Consulting | Type: Permanent Help financial services organisations turn AI ambition into practical business transformation The Role Join Capco’s Business Consulting practice, supporting leading financial services organisations as they adopt and scale AI capabilities across their businesses. This role sits at the intersection of business transformation, AI enablement, and delivery consulting, helping clients identify practical opportunities to embed tools such as GPT, Copilot, and broader AI/ML solutions into day-to-day operations. You will work closely with stakeholders across business, operations, technology, risk, and compliance teams to support the delivery of AI-enabled transformation initiatives. The role combines elements of business consulting, change management, project delivery, and AI commercialisation, with a strong focus on helping organisations confidently and responsibly adopt emerging technologies through practical, human-led delivery. What You’ll Do Support financial services clients in identifying and delivering AI-enabled opportunities that improve operational efficiency, employee productivity, and business innovation using approved AI tools and practical automation where they add value. Partner with stakeholders to translate business challenges into practical AI use cases, supporting workshops, requirements gathering, delivery coordination, and implementation activities. Contribute to AI transformation initiatives across Banking & Payments, Capital Markets, Wealth & Asset Management , or Insurance, helping clients embed AI into workflows, operating models, and business processes. Work alongside cross-functional teams including product owners, engineers, data specialists, risk, and compliance teams to support the testing, validation, and rollout of AI-enabled solutions with human-in-the-loop review and appropriate controls. Deliver stakeholder eng

Build something people love Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work . The Sales Data team is responsible for supporting the entire Commercial team through data modeling, pipelining, dashboarding, experimentation, analyses, and machine learning models. Our stakeholder teams are diverse, including Financial Planners & Advisors, Business Development Representatives, our AI Voice Agent team, Revenue Operations and Commercial Systems. We are looking for a Senior Data Scientist who has strong foundations in data modeling and machine learning to lead high priority initiatives, take ownership as a decision science expert, and help shape the direction of our Commercial team and our AI Voice Agent program. Some of your projects may include: modeling sales data, creating and improving reporting for business stakeholders, exploratory data analysis to improve our sales processes, and developing and maintaining ML models. Our models are used to solve real business problems and directly impact Wealthsimple’s north star metric. Therefore, experience with supporting sales is a bonus. In this role, you will have the opportunity to: Build and maintain new data models that are accurate and reliable Work closely with a wide range of stakeholders from Data Science, Commercial Leadership, Sales Operations, Product, Design, and Engineering Define, prototype, implement and improve ML models Design experiments to test hypotheses (e.

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As a Marketing Analytics Manager, you'll be a senior individual contributor who transforms data into insights and drives decisions and strategy across our marketing channels. You'll own measurement and analytics for campaigns, partners, and field marketing—including attribution modeling, ROI optimization, and emerging AI capabilities—serving as the go-to analytics expert and thought partner for marketing leadership. What You'll Do Drive attribution modeling and full-funnel measurement across all marketing channels, with attention to paid media Connect Paid Ads activity with outcomes on the website and the demand gen funnel to create a holistic view of ad performance Create insights around organic and paid traffic and engagement, with increased scrutiny on GEO Translate data into actionable insights and recommendations for marketing leaders across the business Create forecasts and scenario models to inform annual budget planning and incremental asks Build and maintain self-service dashboards in Tableau for paid media, brand, demand gen, digital, and strategic events Partner cross-functionally with Field Analytics, Strategy & Planning, Marketing Leadership, and Data teams on performance narrative and QBRs Partner with the Marketing Data Operations team to maintain data quality across martech systems Implement AI/ML capabilities for predictive modeling and automated insights Design and support marketing experiments with rigorous testing

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As Sr. Manager, Marketing Analytics, you'll be a senior individual contributor who transforms data into insights and drives decisions and strategy across our marketing channels. You'll own measurement and analytics for campaigns, partners, and field marketing—including attribution modeling, ROI optimization, and emerging AI capabilities—serving as the go-to analytics expert and thought partner for marketing leadership. What You'll Do Drive attribution modeling and full-funnel measurement across all marketing channels Translate data into actionable insights and recommendations for marketing leaders across the business Create forecasts and scenario models to inform annual budget planning and incremental asks Build and maintain self-service dashboards in Tableau for brand, demand gen, digital, and strategic events Partner cross-functionally with Field Analytics, Strategy & Planning, Marketing Leadership, and Data teams on performance narrative and QBRs Partner with the Marketing Data Operations team to maintain data quality across martech systems Implement AI/ML capabilities for predictive modeling and automated insights Design and support marketing experiments with rigorous testing and statistical validation Mentor and provide analytical guidance to junior analysts, and establish best practices for the broader analytics function Stay current with analytics tools and methods to drive competitive advantage What We're Looking For Experience: 8+