Sourcer in London

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe

Here's a summary of the role Data is only powerful when everyone agrees what it means. This is your chance to build a world class product behavioural data system and process from the ground up. We're rebuilding the internal product our teams use to measure product success and end-user value across all our 24+ products in four business units. You'll design the single source of truth: the metric definitions, the telemetry standards, the data contract engineering instruments against, the change governance processes and tooling, and the models that turn behaviour into portfolio insight. You'll educate and support the teams using this internal behavioural data product to set expectations and and plot a rational roadmap for the maturing of this product, helping our user to use the data honestly and wisely. Usage tells you what happened, not why, or whether it mattered. We want someone who sets quantitative behaviour against qualitative evidence and treats the disagreement as the interesting part. AWS/Snowflake is our spine; capture and BI are open decisions you'll help make. Your models feed the business reviews our executive team, CTO and investors use to run the portfolio, and engineering is committed to instrument against your contract. Here's what your first twelve months should look like First 90 days. Learn the estate, meet the engineers who instrument it, and agree the measurement model for one product end to end — with a defensible adoption number and the qualitative read on what it means. Three to six months. Data contract published, instrumentation spec landed with engineering, first business unit building against it. Definitions, naming and versioned change control governed. Six to twelve months. Rolling out across the remaining business units through the BU-aligned analysts, portfolio reporting running on your numbers. Here's a breakdown of what you'll do (not all

About The Role The Director, Strategic Alliances, EMEA will be responsible for defining and executing Diligent's partnerships strategy across the EMEA region as a senior individual contributor. This role will focus on identifying, structuring, and closing high-impact strategic partner-led deals that accelerate customer acquisition, expand Diligent's enterprise footprint, and drive revenue growth through partner resell and co-sell motions — with a particular focus on advisory and consulting firms (Big 4 and Tier 2) and large resellers/channel partners. This senior leader will develop deep insight into regional market dynamics and build the foundational partner ecosystem across advisory/consulting firms, resellers, and channel partners at the pace needed to match Diligent's rapid growth. This is fundamentally a builder's role — the person in this seat will need to build and own the region and its relationships largely from the ground up. This role requires close collaboration with Sales, Product, Marketing, and Customer Success teams. Success will be measured by partner-sourced and partner-influenced revenue, new logo acquisition, expansion of product usage through partners, and the establishment of scalable partnership models that can be operationalized as the business grows. Responsibilities Partnership Strategy & Execution Execute the EMEA partner strategy in alignment with Diligent's global objectives and regional go-to-market plans. Identify, prioritize, and secure strategic partnerships across advisory/consulting firms (Big 4 and Tier 2) Develop partner value propositions, commercial frameworks, and engagement models tailored to EMEA market needs. Establish repeatable partnership structures, playbooks, and success metrics that can scale over time as the region and partner base grow. Channel & Revenue Impact Drive partner-sourced and partner-influenced p

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. A little bit about the role Over the past 18 months, The Dot Collective has successfully established a dedicated Data Architecture practice , laying the foundation for robust, scalable, and innovative data solutions. This practice underpins our commitment to delivering high-quality, data-driven outcomes for clients across diverse sectors. As we continue to grow, we are seeking a Data Solution Architect to play a pivotal role in shaping and implementing cloud native data and AI platforms that make a real impact. Your Key Skills and Capabilities Work with technical teams to clarify and refine architecture so as to maintain consistency during deliver Recognise ways to describe the structure and behaviour of applications used in a business, with a focus on how they interact with each other and with business users or actors Help the customer articulate their requirements and formulate a suitable solution architecture Proven experience of designing and building data platforms. A strong understanding of modelling data and how to make data work at scale A grasp of modern data governance is also appreciated Have an understanding of Microservices and Serverless architectures. Be able to describe the structure and behaviour of the technology platform that underpins user applications and understand on-premise, Cloud hosting and end-user compute Knowledge of open source, open standards and cloud technologies An understanding of architectural concepts, methodologies and approa

Agents have changed the game for software delivery and efficacy. Diligent is the leading GRC platform in the world, and we are racing ahead to take the agents show on the road and work with the customers where they work . The FDE function will lead the change on how we embed AI agents into some of the world’s most complex governance, risk and compliance environments. This is not a support or consultancy role. It is a builder role, for someone who is equally comfortable reading a failing agent trace, running a discovery workshop with a bank’s internal audit team, and translating what they find into a production-grade agentic solution. You will be building AI agents for GRC professionals , not assistants that surface suggestions, but agents that own complex, multi-step workflows end to end . Agents that customers can hand a task to and trust it will come back done. Closing the gap between a promising prototype and something a company Board and ELT depends on is a completely . Here’s a breakdown of what you’ll do Embed directly with major enterprise customers (global banks, regulated corporates) across EU and US ; sitting wi th internal audit teams, risk functions, compliance and governance professionals to understand their real workflows and devise agentic solutions to intelligently automate them creating tremendous efficacy and efficiencies for our customers. Run agent-focused discovery workshops, rapidly prototype agentic solutions, and test them with practitioners; distinguishing between workflows that need an agent and those that need a button. Source, integrate, and move data between enterprise systems as part of live customer implementations — understanding the real data landscape customers operate in and building reliable pipelines to support it . Take agents from prototype t

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. As a Product & Privacy Counsel at Synthesia, you’ll partner closely with Product, Engineering, R&D, Business Operations, and Go-To-Market teams to help bring innovative AI products to market responsibly. Reporting to the Head of Product & Privacy Legal, you’ll play a key role in navigating complex legal and regulatory issues, balancing risk with business objectives, and helping the company scale with confidence. In this role you will: Partner with Product, Engineering, and R&D teams across the entire product lifecycle to identify and address legal risks in areas including AI, IP, privacy, security, open source, and marketing. Support commercialization efforts by advising Go-To-Market and Business Operations teams on product positioning, licensing models, and regulatory issues. Monitor and interpret evolving laws related to AI, privacy, IP, and competition to ensure proactive compliance and business alignment. Draft and maintain scalable processes, playbooks, and guidance to support consistent legal input across teams. Assist in creation and management of privacy, security and AI governance frameworks and audits. Operate independently and provide pragmatic, business-oriented legal advice that alig