Senior Ai Ml Data Model Architect Jobs

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 . ML Platform & Infrastructure Team The Machine Learning Infrastructure & Platform team builds the foundational architecture powering AI and GenAI initiatives across Wealthsimple. We sit at the intersection of production MLOps and cutting-edge GenAI enablement. As our AI footprint expands rapidly, our priority is evolving our robust MLOps foundations into a scalable, high-performance LLM serving and routing platform. We build self-serve systems that allow Data Scientists and Engineers to host open-source LLMs reliably, optimize inference latencies, manage GPU infrastructure, and benchmark model performance safely in production. The Role We are looking for an experienced MLOps or ML Platform Engineer who is excited to pivot their deep background in model orchestration, serving, and platform tooling toward solving the unique challenges of LLM inference and infrastructure . In this role, you will bridge the gap between traditional MLOps (model lifecycles, pipeline orchestration, serving infrastructure) and modern GenAI stack requirements (vLLM, GPU cluster management, intelligent model routing, and automated Evals). You will take end-to-end ownership of setting the technical direction for operating enterprise-grade LLM systems company-wide. In this role, you will have the opportunity to: Turn MLOps expertise to GenAI: Transition traditiona

RDQ127R59 Summary As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers. Impact You Will Have Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques. Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks. Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency. Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments. Minimum Qualifications Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc). ML Experience: Strong background in building, training, and deploying machine learning models in production. Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks. Core Coding: Proficiency in Python, Scala, or Java. Preferred Skills Advanced Education: PhD in AI, Data Science, or a related technical discipline. Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment. Systems Domain:

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. What You’ll Do: Architect the Future of AI Infrastructure: You will design, build, and own the end-to-end platform that supports the entire lifecycle of our ML models—from massive-scale distributed training to ultra-low-latency, highly-available inference. Optimize and Serve Cutting-Edge Models: You'll implement and scale sophisticated inference stacks for LLMs using frameworks like vLLM, TensorRT-LLM, or SGLang . You’ll solve complex challenges in throughput, latency, token streaming, and automated scaling to deliver a seamless user experience. Empower AI Innovation: You will act as a strategic partner to our AI Research and Data Science teams. You’ll create a seamless developer experience that accelerates their ability to experiment, fine-tune, and deploy groundbreaking models with velocity and confidence. Automate Everything: You'll develop robust CI/CD/CT (Continuous Training) pipelines using tools like Argo Workflows, ArgoCD, and GitHub Actions to automate model validation, deployment, and lifecycle management, ensuring our systems are both agile and rock-solid. What are we looking for Experience: 5+ years in infrastructure or software engineering, with at least 2+ years laser-focused on MLOps or ML infrastructu

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is seeking a Senior Director of Consumer Data Science to lead a multi-team organization that partners across Consumer, Product, Engineering, and the broader business. You will set the strategy and operating model for consumer data science, strengthen the systems and standards that make scientific outputs reliable, actionable, and scalable, and guide high-impact decisions through measurement, experimentation, causal inference, and ML. This leader will help define how Reddit measures and improves relevance across the consumer journey—from retrieval and ranking to feed, search, recommendations, and community discovery—and will shape the organizational capabilities required to advance these systems over the long term. Accordingly, the role requires the technical depth to evaluate architecture and analytical investments, guide state-of-the-art ML system improvements, and the leadership presence to align senior leaders around difficult tradeoffs. What you’ll do Partner with senior leaders across Consumer, Product, Engineering, and business functions to define company-level bets, priorities, and tradeoffs. Set the data science strategy for Reddit’s feed, recommendation, search, retrieval, and ranking systems, including objective design, candidate generation, ranking quality, relevance evaluation, experimentation, and long-term optimization. Establish the measurement and experimentation framework for relevance optimization, including offline evaluation, online experimentation, counterfactual analysis, guardrail met

Who we are Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung. Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts. Our 1,800 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients . What you will be doing As a Senior Data Scientist in our London office , your role will encompass: Designing and implementing advanced data science and machine learning solutions to solve complex business problems. Taking ownership of project streams, from defining technical deliverables and timelines to presenting updates to client steering committees. Supervising and mentoring team members on code, deployment, and best practices. Architecting and deploying robust, scalable solutions using modern cloud technologies and MLOps principles. Qualifications Necessary education and experience Education : A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field. Project & Team Leadership : Demonstrable experience supervising team members, taking responsibility for project delivery, defining technical tasks, and presenting project updates to both internal and client stakeholders. Advanced Modelling : Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference. ML-Ops & Orchestration : Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines. Programming & Data Engineering : Proficiency in objec

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 In this role, you will be a member of the Perception & Behavior team, leveraging the cutting edge of machine learning research to solve challenging real-world robotics problems. This role is focused on bringing advancements in the field of ML and large-scale learning to the AV domain, moving towards a more end-to-end autonomous driving system. This role requires working with and developing large models for perception and behavior, keeping up-to-date and experimenting with state-of-the-art architectures quickly and efficiently, collaborating with other teams to determine data and infrastructure support needs, and working to improve model optimization and inference speeds. You will use your applied research skills to think through the creation and deployment of these ML models on our autonomous vehicles while working alongside talented researchers in the field. If you love solving fundamental AI challenges and deploying your s

Senior Data Scientist Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We are looking for a Senior Data Scientist to join Capco’s growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes while mentoring others and collaborating in a dynamic, multi-disciplinary environment. You'll also embrace AI-enabled ways of working, using approved AI tools where appropriate to enhance delivery while applying sound professional judgement. What You’ll Do Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments. Develop and prototype ML models to solve complex business challenges using modern techniques and tooling. Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables, using approved AI tools where appropriate to improve efficiency and accelerate insight. Guide and coach data science pods, supporting skill development and solution design. Act as a subject matter expert on ML architecture, model calibration, and productionisation, promoting responsible AI practices and scalable model governance where applicable. What We’re Looking For Hands-on experience building and deploying data science solutions in Python and related ML libraries. Strong background in applied machine learning, model development, and data engineering, with an appreciation of responsible AI principles. Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, and Redshift. Demonstrated ability to lead cross-functional teams and mentor junior practitioners. Ability to communicate complex technical concepts clearly to non-technical audiences and apply AI-enabled approaches to deliver practi

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

Senior Machine Learning Engineers at Thoughtworks build, maintain and test the architecture and infrastructure for managing machine learning applications. They are involved in supporting and contributing to the design of the end-to-end applications and products. They are responsible for building core capabilities including technical and functional machine learning systems and applications, being the anchor for functional streams of work and are accountable for timely delivery. As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy. Due to the nature of the projects and specific client security clearance, this role requires the successful candidate to be a Singapore Citizen or PR of Singapore. Job responsibilities You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives You wil

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: 5+ years of experience in ML infrastructure, including model training and model deployments Hands-on experience with ML optimization, including memory and GPU profiling Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are looking for a hands-on Full-Stack Senior Software Engineer to join our IT Software Engineering team reporting directly to the Director, IT Software Engineering. Inside IT Software Engineering, we are shifting from a traditional "SaaS-only" procurement model to an agile Build and Buy strategy. Powered by the Elastic Stack—Elasticsearch, Kibana, Elastic ML, and native AI capabilities—our team builds custom, enterprise-grade applications and AI-powered bots for internal teams (IT, HR, Finance, Ops), replacing expensive third-party software contracts with faster, native solutions. This is a 100% individual contributor (IC) engineering role . You will lead the technical design, development, and deployment of full-stack internal web applications and conversational AI bots. You will write clean React and Node.js code, integrate backend services natively with Elasticsearch, and leverage modern AI development tools (Cursor, Claude, Copilot) to accelerate delivery—all while taking complete operational ownership of production systems. What You Will Be Doing Build Enterprise Applications: Write clean, maintainable code across React, TypeScript, and Node.js to design and ship full-stack applications that replace legacy SaaS tools. Develop AI Bots & Workflows: Architect and deploy intelligent internal bots using LLMs, Retrieval-Augm

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. The Impact You’ll Make at Appier We’re looking for a Staff/Senior Machine Learning Platform Engineer to join our Machine Learning Platform Team, which powers end-to-end infrastructure for model training, evaluation, deployment, and monitoring at scale. Our platform supports daily execution of hundreds of ML models and processes billions of data records across batch and streaming pipelines. In this role, you’ll shape the architecture and core components of our ML platform—covering batch (Spark), streaming (Flink), job orchestration (Argo on Kubernetes), and infrastructure tools—while ensuring the platform remains robust, scalable, and developer-friendly. You’ll also champion best practices and modern development tools including LLM-based programming assistants. What You’ll Work On Architect, implement, and scale batch (Spark) and streaming (Flink) pipelines that process billions of records daily for ML training and evaluation. Design and operate robust ML job execution frameworks for training, inference, and post-processing. Build and maintain internal API servers and developer tools to orchestrate ML jobs on Kubernetes (via Argo Workflows, Helm, Terraform). Design and monitor data infrastructure using ClickHouse and PostgreSQL. Ensure high availability and observability through monitoring tools like Prometheus and Grafana. Collaborate with data scientists, product managers, and engineers to deliver reliable and efficient ML platform capabilities. Actively adopt and promote the use of LLM-based tools (e.g.,

About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com . About the Role We’re on the lookout for an ambitious and technically outstanding Senior Software Engineer, Backend Development to join our Enterprise Solution Engineering Team, Product Recommendation (ES REC) . Software engineers at Appier build a wide range of platforms and services that interconnect data and AI with our customers and users. In this role, you will be at the forefront of AI innovation, designing and building scalable backend architecture that delivers personalized experiences. What You’ll Do Key owner of sizable engineering projects and services within the ES REC team. Architect and implement AI Agents and agentic workflows to automate decision-making processes and enhance recommendation delivery. Build and optimize Machine Learning pipelines for large-scale personalization, ensuring efficient data processing, model serving, and low-latency response. Design and operate scalable, cloud-native architectures leveraging managed services (e.g., GKE, BigQuery, or Pub/Sub ) to support high-throughput recommendation workflows. Architect and operate resilient ML job execution frameworks covering training, inference, and post-processing workflows to ensure system elasticity. Define and implement CI/CD pipelines with tools like Jenkins or ArgoCD to enable seamless, automated, and reliable deployments. Lead system designs and provide technical guidance to team me