Senior Ai Ml Data Model Architect Jobs

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. You'd be joining the Artificial Intelligence team . We own the algorithmic core of the platform: Predictions, Contextual Personalization, contextual bandits, autosegmentation, and the agentic workflows behind Loomi. We work with behavioural data at terabyte scale, across 1,400+ customers, in production, every day. You'll work on cutting-edge technologies, impacting millions of users, and contributing to a product that truly makes a difference. Working in one of our Central European offices (Bratislava, Brno, Prague) or from home (Czechia, Slovakia) on a full-time basis , you´ll become a core part of the Engineering Team . The mission You turn a model that works in an experiment into a service that works for 1,400 customers. You own ML-powered features end to end — the API that configures them,

About the Role The Senior AI Evals Test Engineer is a hands-on technical role responsible for defining, developing, and executing robust evaluation frameworks and test strategies for AI agents built using the Google Agent Development Kit (ADK) or similar sort of agentic frameworks . This role bridges AI development and reliable deployment — ensuring our agents are safe, ethical, effective, and meet high-quality performance standards. A significant focus of the role is on Responsible AI and Safety Evals, including adversarial testing, red-teaming, bias detection, and toxicity measurement . The engineer will design scalable evaluation pipelines , build synthetic test environments, and work closely with AI/ML Engineers, Researchers, and policy teams to ensure agents are production-ready and compliant with regulatory and ethical standards. The role is 70% Automation and 30% Manual Testing , and sits within the Applied AI: Test Engineering team as a key technical authority. Key Responsibilities Design and build agent evaluation frameworks — create end-to-end infrastructure for evaluating LLM-based agents across correctness, latency, cost, safety, and task completion rate Build synthetic testing environments and simulation strategies to stress-test AI agents under diverse real-world conditions, with specific focus on agents built on Google ADK and related Google AI/ML services (e.g., Vertex AI, Gemini models) Build golden datasets and test harnesses — curate domain-specific evaluation sets for Rubrik's product verticals (data security, SaaS protection, cyber recovery, compliance) Establish eval-as-a-service — build and enhance centralized evaluation platform that any IT team members can self-serve to test their agents against standardized and custom benchmarks Automate regression and drift detection — implement CI/CD-integrated eval pipelines that catch regressions on every model or prompt change before production deployment Define eval taxonomies and rubrics — est

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As Senior Technical Program Manager for the Human-in-the-Loop (HITL) Operations , you will own the end-to-end lifecycle of Roblox's AI data labeling and model evaluation ecosystem. This is a high-leverage, high-ownership role at the intersection of Research, Engineering, and Operations. You will scale our data operations that is handling million of items evaluated annually today with projection of 4x the current volume by 2030, managing a multi-million annual budget and a distributed workforce of 100+ remote contractors — all while driving the platform evolution from manual workflows to AI-assisted, LLM-accelerated operations. This is a rare opportunity to build the data infrastructure that directly determines the quality of Roblox's AI models across creator tools, content discovery, in-experience AI, and 3D generative content — at the exact moment when human judgment is the critical ingredient for getting these models right. You Will Lead data programs end-to-end. Own the full lifecycle of labeling and model evaluation workflows across Roblox's AI teams — from translating ambiguous ML requirements into structured annotation tasks, to overseeing contractor execution, quality review, a

Senior GenAI Engineer Location: Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Build and scale cutting-edge generative AI solutions that drive real business impact The Role As part of Capco’s Technology Delivery Team, you will bring hands-on experience in agile delivery and engineering best practices to develop innovative AI-driven solutions. As a Senior GenAI Engineer, you will contribute across the full AI lifecycle—from experimentation and prototyping through to production deployment—helping deliver scalable, high-impact solutions for financial services clients. What You’ll Do Design and build applications using foundation models and modern GenAI techniques (e.g., RAG, agent-based workflows) Develop and experiment with autonomous or semi-autonomous agent frameworks Contribute to full-stack AI solutions, including backend services, APIs, and user-facing components Deploy and scale AI/ML solutions in cloud environments (AWS, Azure, or GCP) Collaborate with cross-functional teams and support knowledge sharing across the team What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field (or equivalent experience) ~5+ years of software engineering experience with exposure to AI/ML or data-driven applications Hands-on experience with LLMs or generative AI Strong Python skills and experience building scalable backend systems Experience working with cloud platforms and modern development practices Willingness to work in our office 3 days/week Bonus Points For Experience with GenAI concepts such as RAG, embeddings, vector databases, or agent-based systems Familiarity with MLOps/LLMOps tools and model lifecycle management Experience contributing to full-stack development across backend and frontend Interest in staying current with emerging AI trends and technologies Experience mentoring or supporting team development Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions W

Senior GenAI Engineer Location: Charlotte, NC | Practice Area: Technology & Engineering | Type: Permanent Build and scale cutting-edge generative AI solutions that drive real business impact The Role As part of Capco’s Technology Delivery Team, you will bring hands-on experience in agile delivery and engineering best practices to develop innovative AI-driven solutions. As a Senior GenAI Engineer, you will contribute across the full AI lifecycle—from experimentation and prototyping through to production deployment—helping deliver scalable, high-impact solutions for financial services clients. What You’ll Do Design and build applications using foundation models and modern GenAI techniques (e.g., RAG, agent-based workflows) Develop and experiment with autonomous or semi-autonomous agent frameworks Contribute to full-stack AI solutions, including backend services, APIs, and user-facing components Deploy and scale AI/ML solutions in cloud environments (AWS, Azure, or GCP) Collaborate with cross-functional teams and support knowledge sharing across the team What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field (or equivalent experience) ~5+ years of software engineering experience with exposure to AI/ML or data-driven applications Hands-on experience with LLMs or generative AI Strong Python skills and experience building scalable backend systems Experience working with cloud platforms and modern development practices Willingness to work in our office 3 days/week Bonus Points For Experience with GenAI concepts such as RAG, embeddings, vector databases, or agent-based systems Familiarity with MLOps/LLMOps tools and model lifecycle management Experience contributing to full-stack development across backend and frontend Interest in staying current with emerging AI trends and technologies Experience mentoring or supporting team development Why Join Capco Deliver high-impact technology solutions for Tier 1 financial

P-1377 Mission As a Senior ML and AI Technical Solutions Engineer, you play a critical role by helping customers debug and maintain stable GenAI and ML Workloads with AI agent systems using the Databricks Platform. You will develop product expertise end-to-end by advising a broad set of customers and use cases across the space - including products such as Agent Bricks, Vector Search and Model Serving. You will collaborate cross-functionally with other teams - whether that’s working with engineering to improve the product or interacting directly with the account team on a specific customer issue. TSEs have proven production troubleshooting and optimisation experience to help our customers’ workloads run smoothly and to achieve their strategic objectives with ML/AI technology with Databricks. Additionally, you are an early adopter of GenAI technology to improve your own efficiency and amplify the team's output. Reporting to a TSE manager - you will be part of a world class global support engineering organization for Databricks, known for your technical depth and delivering impeccable customer service. The Impact You Will Have Act as senior technical solution expert for complex issues spanning data pipelines, ML pipelines and/or AI applications, applying deep expertise in distributed systems. Analyse and troubleshoot production workloads at the code level, optimise for performance, reliability, latency, and cost. Diagnose and support Machine Learning and/or Large Language Model deployments, including real-time and batch inference, autoscaling, monitoring, logging, and alerting. Serve as a Subject Matter Expert guiding customers on experiment tracking, model registry, versioning, evaluation, labelling, tracing, and lifecycle observability. Provide high-quality support by guiding customers in leveraging Databricks AI to solve generative AI use cases & challenges, leveraging LLMs, MCP, AI Agents, RAG/Agentic RAG, APIs, vector embedd

This is Adyen At Adyen, we’re engineered for ambition. We empower our teams with the culture and support they need to own their careers. The people of Adyen are motivated problem-solvers who tackle unique technical challenges at scale, delivering innovative and ethical solutions to help businesses achieve their ambitions faster. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Senior Machine Learning Engineer Adyen is looking for a Senior Machine Learning Engineer to join our Anti-Money Laundering team in Amsterdam, someone with experience of building and operating robust machine learning systems at scale in production environments. The Anti-Money Laundering team processes a massive transaction volume (over 800B euro in H1 2026) to detect complex financial crime and cover a wide range of customer risks. We currently run a hybrid stack of business rules and machine learning models, with a clear mission to systematically reduce our dependence on static rules and transition to a modern, model-first detection engine. In this role, you will: Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment Help us upgrade an existing rules-heavy system to a modern automated AI/ML engine Collaborate with data engineers and data analysts to develop best in class Fintech models Collaborate with operations and compliance teams to ensure Adyen’s models operate worldwide without a hitch Tackle difficult technical challenges like extreme class imbalance and incomplete ground truth Support and encourage good engineering practices Who You Are: You have 7+ years of experience as an engineer working in th

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We’re a team of high-output generalists where ML and systems engineering converge. This is not a "run the models" role. We reason from first principles about why a perception model learns what it learns, close the gaps that cap its performance, and raise the bar on the data and evaluation loop that drives autonomy. Your work will directly impact how autonomous systems understand rare scenarios, adapt to global geographies, and scale safely. About the work You’ll solve autonomy’s hardest data challenges through applied ML and systems rigor: Diagnose why perception models underperform on the long tail, and turn that into targeted data and training priorities. Design eval metrics and regression detection that tell us whether a model is ready. Curate and clean training data for segmentation and occupancy; hunt the data problems that silently cap performance. Run controlled ML experiments and ablations; cleanly sepa

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Nuro takes a machine-learning-first approach to autonomous driving technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data. The team plays a crucial role in the advancement of autonomous driving systems by creating a scalable and reliable data infrastructure. This infrastructure is designed to produce training and evaluation data derived from both on-road collected logs and simulation logs. Additionally, the team collaborates closely with system engineers to thoroughly validate the autonomous driving system before its deployment. About the Work Design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation. Create and implement a storage system capable of accommodating both the large volume and diverse range of e

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other parameter-efficient methods) where they match frontier quality, and know when they don't. Predictive difficulty. Build models that estimate how hard a task is for frontier systems before running a single rollout. Measurement for AI data. Build golden datasets, quantify the accuracy and calibratio

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! The Role We are seeking a highly technical and strategic Senior Product Manager with deep AI/ML expertise to lead development across our agentic data systems, synthetic data systems, evaluations, and data-acceleration initiatives. This role is ideal for someone with a core ML/AI product background, strong familiarity with model development workflows, and demonstrated success delivering product experiences that improve the speed, quality, and scalability of data operations. You will work closely with Research, Engineering, Data Operations, and Design to define product vision, roadmap, and execution plans for intelligent workflow systems that optimize data pipelines, improve task quality, and enable faster and more efficient delivery of AI-ready datasets. This is a highly cross-functional, technically deep IC role with broad surface area and significant impact. You will lead initiatives spanning multiple teams, balancing near-term execution with long-term platform evolution. What You’ll Do Own the product vision, strategy, and roadmap for the task and Expert Contributor Evaluations product supporting internal and external platform users. &nbsp

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior ML Engineer, you'll play a central role in building the data science behind the products — from framing new fraud, risk, and intelligence problems, to designing and deploying ML models at scale, to helping our enterprise customers and go-to-market teams understand and act on the insights we generate. What you’ll do: Design, build, and continuously improve the ML models that power our risk and intelligence products, and take ownership of new signals as they get scoped. Take a loosely defined business or customer problem and break it into a clear data problem, articulating value, impact, and complexity before proposing a solution. Build anomaly detection, fraud, and risk-modeling approaches — including network/graph-based methods — that keep our signals accurate and resistant to adversarial behaviour. Own model development, deployment, and monitoring end-to-end, partnering with ML/data engineers on scalability, reliability, cost, and dashboards/alerting. Design and run experiments (A/B tests, offline customer POCs) to validate new signals before they roll into production. Manage and analyse large, multi-country datasets, ensuring data integr

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We are a team of high-output generalists where ML and systems engineering converge to push autonomy performance forward. As a Senior Perception ML Data Infrastructure Engineer, you will own the critical bridge between our autonomous vehicle hardware, our human labeling operations, and our ML models. You will take ownership of our core native perception data platform. This is not a standard web development role; the stack is deeply adjacent to our core robotics infrastructure. You will be dealing with massive, dense 3D point clouds at a scale that pushes the boundaries of industry state-of-the-art, alongside complex sensor parsing, pipeline propagation, and rigid performance constraints. You will operate in highly ambiguous environments, inheriting complex systems, establishing strict API boundaries, and building the "good enough, fast enough" infrastructure that guarantees our ML models learn from high-quality data. About the wo

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Team The Perception ML Operations team sits at the center of how Nuro's vehicles learn to see. We are responsible for the training and evaluation data that powers perception models across every sensor modality: vision, lidar, radar, and beyond. We work alongside ML engineers, product owners, data engineers, and external labeling partners to turn ambiguous, fast-moving requirements into data deliverables the Perception team can build on with confidence. This is a team that operates at the intersection of ML urgency and operational discipline. Here is what the work actually looks like day-to-day: Sitting in a roadmap review, hearing a new feature requirement land, and walking out with a concrete data collection and labeling plan already scoped against timeline and budget. Reviewing vendor throughput against milestone dates and catching a capacity gap before it would become a release risk. Querying pipeline data directly to unders