
9fin · London
About 9fin 9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion. Debt markets are vast, global, and mi...
About 9fin
9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion.
Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces
this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value
workflows across global markets.
Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms,
law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention
driven by deep workflow adoption.
We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward
becoming the category-defining platform for debt markets worldwide.
The Data Science team is growing at 9fin! We are doing world-class work with groundbreaking technologies to build data-driven
products using machine learning, computer vision, natural language processing, speech and audio, and knowledge/data mining. We are
looking for a Senior AI Engineer to accelerate our application of AI across teams and products. Come and join us, you will get to
build large-scale AI powered systems, learn and apply the latest techniques, and work alongside other great researchers and
engineers!
Every day is different, but here's an example of the kind of things you'll work on:
models to deliver innovative, practical solutions that streamline decision-making and unlock new efficiencies.
managed model delivery/deployment.
adoption of AI throughout 9fin.
This role is focused on improving the models themselves. While experience with retrieval systems, knowledge graphs, and AI
applications is valuable, the core challenge is building proprietary financial-domain models that outperform general-purpose LLMs
on the workflows that matter most to 9fin users.
Gemma for production use cases.
adaptation to improve model performance on specialised tasks.
data, and creating data flywheels that continuously improve model quality.
real-world model performance.
debt instruments, filings, court documents, and capital markets workflows.
acceleration, and cost-performance trade-offs.
operating costs.
model monitoring in production environments.
We’re a scaling start up, and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We
also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel.
Financial & Insurance
Time off
Training & Culture
9fin is an equal opportunities employer
At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential
and truly belong. We recognize that building diverse teams enables a more creative and productive environment. If you’re excited
about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway. You might
just be who we’re looking for — either for this role, or perhaps another.
About us: Causaly is redefining how humans acquire knowledge and develop insights in biomedicine. Our AI-powered platform enables researchers and decision-makers to discover and interpret evidence from millions of scientific publications, clinical trials, regulatory documents, and other complex data sources in minutes. We are building the world’s most advanced biomedical knowledge platform, powered by a high-precision Knowledge Graph and GenAI capabilities. Our technology is already used by leading biopharmaceutical organizations to accelerate drug discovery, improve safety, and drive better decision-making. Backed by top-tier investors including ICONIQ, Index Ventures, Pentech, and Marathon, we are scaling rapidly and expanding our product suite and market presence. ABOUT THE TEAM We’re hiring AI engineers to help us transform research outcomes in biomedical sciences. We utilise generative AI and agents to help scientists find novel connections and insights from biomedical literature and datasets. Delivering a faster research experience is not just a matter of picking the latest LLM model. Getting accurate, scientifically relevant, trustworthy and meaningful results relies on building trust with our users that comes from integrating proper levels of guardrails, biomedical curation, consistent update cycles and robust deployment practices that make our platform a one-stop shop for a researcher’s needs. We’re looking for AI engineers who will champion this cause and help us apply AI to transform the way biomedical professionals carry out their research and day-to-day exploration. WHAT YOU’LL BE DOING · Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver measurable impact. · Apply strong software engineering principles, such as modularity, testing, code reviews, CI/CD and observability, to ensure AI systems are reliable, maintainable, production-ready and can be readily adapted to future developments. · Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance. · Collaborate closely with product, design, and other engineering teams to scope work, align on success metrics, and incrementally ship improvements in user-facing features powered by AI. · Document system architectures and decision rationale early and clearly, enabling alignment across teams and accelerating onboarding and iteration. · Champion model and data quality, including dataset versioning, robust evaluation, fairness/bias assessment, and real-world performance tracking. · Mentor junior AI engineers and cross-functional teammates, sharing best practices in modelling, coding, maintaining and integrating product features, and helping grow a high-trust, high-performance team culture. · Stay up-to-date with emerging research and tools, distilling key insights and bringing back relevant innovations to elevate team capabilities and product opportunities. · Contribute to a culture of knowledge sharing, through company-wide Slack channels, Show and Tell presentations and technical deep-dives. WHAT EXPERIENCE YOU’LL NEED TO BE SUCCESSFUL · A master's degree or above in Computer Science, Electrical Engineering or a related field. · 5+ years of experience building AI/ML systems in production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring. · Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. · A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine-tuning. · Strong software engineering foundations such as version control, unit/integration testing, CI/CD, containerization plus a mindset of building for reliability and scale. · Experience working in product-focused teams, collaborating with designers, engineers, and PMs, to scope and ship AI features iteratively · Ability to reason about system behavior end-to-end, including model performance, latency, and observability, and how these impact user experience. · Clear, structured communicator, comfortable documenting and defending architectural decisions and engaging in thoughtful technical debate. NOT REQUIRED, BUT IT’S A PLUS IF YOU ALSO HAVE: · Experience with MLOps/LLMOps frameworks and best practices · A PhD in Computer Science, Electrical Engineering or a related field. · A background or work experience in life-sciences, health-tech, or other data-intensive domains BENEFITS 💰 Competitive compensation package 🩺 Private medical & dental insurance 📔 Life insurance (4 x salary) 🤓 Personal development budget 🧘 Individual wellbeing budget 🌴 25 days holiday plus bank holidays 🥳 Your birthday off! 🚀 Potential to have real impact and accelerated career growth as a member of an international team that's building a transformative AI product. We are on a mission to accelerate scientific breakthroughs for ALL humankind, and we are proud to be an equal opportunity employer. We welcome applications from all backgrounds and fairly consider qualified candidates without regard to race, ethnic or national origin, gender, gender identity or expression, sexual orientation, disability, neurodiversity, genetics, age, religion or belief, marital/civil partnership status, domestic / family status, veteran status or any other difference.
Do you want to build the AI systems that compliance teams rely on to investigate real financial crime? Are you excited about taking agentic workflows from prototype to production at scale? Do you want your work to directly help catch bad actors moving money across blockchains? Elliptic is hiring a Senior AI Engineer to join our AI team. It is the team behind Elliptic's copilot, the AI product that helps compliance investigators trace fund flows, surface patterns, and respond to risk in real time. This role sits at the centre of that work, designing the agentic systems, LLM integrations, and backend services that turn complex blockchain data into useful answers. You'll join a focused team that cares about the quality of what it builds and gives you the space to do your best work. There's real ownership here, breadth across AI and backend systems, and the freedom to turn good ideas into shipped products. The problems are technically challenging, and the work is visible. The impact you will have: As a Senior AI Engineer on the AI team, you'll own significant parts of the Agentic stack that power Elliptic's copilot. You'll lead the design of agentic workflows, drive technical decisions on how we build and operate LLM-based features, and help raise the engineering standard across the team. You'll partner with product, web engineers, and your engineering lead to take complex problems from ambiguity to shipped product, and you'll mentor more junior engineers as the team grows. What you will do: * Design and build agentic workflows and AI-powered features that power Elliptic's copilot, using LLM frameworks such as LangChain or LangGraph. * Lead the design of agents, tool integrations, and retrieval pipelines that turn complex blockchain data into useful answers for investigators. * Build and own evaluation frameworks that measure and improve the quality, reliability, and latency of LLM outputs. * Design and build the backend services, APIs, and event-driven systems that support these features, using TypeScript and Node.js. * Drive technical design reviews and architecture decisions for AI workstreams. * Mentor and coach more junior engineers through pair programming, code review, and design feedback. * Raise the engineering bar across the team by promoting good practices in testing, observability, and AI system reliability. * Influence cross-team decisions on how AI capabilities integrate with the rest of the Elliptic platform. What you will achieve in the first 6 months: * Owned and shipped at least one significant AI capability end-to-end, from ambiguous problem statement through to production. * Driven the technical direction of an AI workstream, including architecture, evaluation, and rollout. * Established or improved at least one team practice for building AI systems (evals, observability patterns, prompt management, rollout safety). * Mentored junior engineers on AI engineering practices and contributed to their growth. * Built strong working relationships across product, web engineering, data engineering, and DevOps. * Started to influence adjacent teams on how Elliptic builds with AI. You will be a great fit here if you: * Care about building AI systems that work reliably in production, not just demos. * Have strong instincts for trade-offs specific to LLM systems: cost vs latency vs quality, deterministic vs probabilistic behaviour, when to use an agent vs a workflow. * Can take ambiguous AI problems and break them into shippable pieces with clear evaluation criteria. * Communicate clearly with non-engineers (product, stakeholders, leadership) about AI capabilities and limitations. * Have coached or mentored other engineers and enjoy raising the bar through reviews, pairing, and feedback. * Are genuinely curious about the domain and find blockchain investigations and financial crime prevention interesting. Our ideal candidate has: * 5-8+ years of software engineering experience, with at least 1-2 years of meaningful production work building LLM-powered features. * Direct experience with LLM frameworks such as LangChain, LangGraph, or similar. * Hands-on experience building agentic systems: tool use, multi-step reasoning, planning, memory, and human-in-the-loop patterns. * Practical understanding of prompt engineering, structured outputs, context management, and managing the trade-offs of working with LLMs. * Experience building and running evaluations for LLM outputs (eval sets, LLM-as-judge, regression testing). * Strong backend skills in TypeScript / Node.js, with solid API design. * Cloud experience (AWS: Lambda, ECS, S3, or similar). * Database proficiency across SQL (Postgres) and some NoSQL exposure. * Demonstrated ability to mentor and coach other engineers. * Uses AI coding assistants (Copilot, Cursor, Claude, etc.) critically and effectively as part of their day-to-day workflow. Bonus points for: * Experience with retrieval-augmented generation (RAG) and vector databases (pgvector, Pinecone, or similar). * Experience designing multi-agent systems and agent orchestration patterns. * Familiarity with LLM observability tools (LangSmith, Langfuse, Arize, or similar). * Experience working with multiple model providers (Anthropic, OpenAI, open-weight models) or with fine-tuning. * Hands-on experience with Terraform, Kubernetes, or infrastructure-as-code tooling. * Experience with observability platforms like Datadog. * Distributed or event-driven architectures (SNS, SQS). * Interest in cryptocurrency, blockchain, or compliance. JOB BENEFITS > How we work: * Hybrid working and the option to work from almost anywhere for up to 90 days per year * £500 Remote working budget to set up your home office space > Learning & Development: * $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development > Vacation/ Leave: * Holidays: 25 days of annual leave + bank holidays * An extra day for your birthday * Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave and leave. > Benefits: * Private Health Insurance - we use Vitality! * Full access to Spill Mental Health Support * Life Assurance: we hope you will never need this - but our cover is for 4 times your salary to your beneficiaries * Cycle to Work Scheme We know Diversity and Inclusion is much deeper than just hiring, but it's important for us to mention it here. We welcome and embrace individuals of all backgrounds and identities at Elliptic, and this is an ongoing priority for us. We know incredible people don't all think in the same way. We want to be challenged every day. We believe our diverse team of individuals underpins this by bringing creative thinking and innovation to Elliptic every day. We are committed to creating a diverse, inclusive and equitable workplace, so we welcome applications from everyone, even if you may not think you fit all of the requirements of our roles. We foster an environment of psychological safety, where everyone feels comfortable to bring their whole self to work.
ReqID: FEQ327R328 Recruiter: Kanwal Matharu Location: London, United Kingdom - Hybrid Skills: Data Science, Machine Learning, AI, LLM, GenAI As a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as an ML expert. You will be reporting to the Manager, Field Engineering (Specialist Team) The impact you will have: * Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services. * Provide advanced technical support to the Solution Architects during the technical sales cycle by building MVPs, leading deep-dive technical sessions, and strategically aligning ML/data science solutions to complex customer business challenges using relevant real-world examples. * Serve as the trusted technical advisor for customers developing GenAI solutions, specializing in the design and implementation of RAG architectures on enterprise knowledge bases, enabling natural language querying of structured data, and establishing content generation and monitoring frameworks. * Drive community growth and platform adoption through thought leadership activities, including the creation of technical tutorials and training materials, as well as leading hackathons and presenting at industry conferences. What we look for: * Experienced, technical, customer-facing, and with a background in Data Science / Machine Learning, and Data Engineering. Looking to learn and develop in a customer-facing technical role as a subject matter expert (SME) in a pre-sales environment. * Pre-sales or post-sales experience working with external clients across a variety of industry markets Data Science/ML Skills * Hands-on industry ML experience in at least one of the following: * ML Engineer: Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring * Data Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI * Hands-on experience working with Distributed Spark based systems. * Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience * Experience communicating and teaching technical concepts to non-technical and technical audiences alike * Passion for collaboration, life-long learning, and driving our values through ML * [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role * [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets * Can meet expectations for technical training and role-specific outcomes within 3 months of hire * Can travel up to 30% when needed About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.