Senior AI Engineer - LLMs and Finetuning

Elliptic

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.

Databricks

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.

Relation Therapeutics

ABOUT RELATION Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. THE OPPORTUNITY Join the Turing team as a Machine Learning Scientist, where you will develop advanced AI systems that help scientists reason about complex biological problems. This role focuses on building LLM-driven reasoning systems and intelligent agents, using approaches such as reinforcement learning, RLHF, symbolic reasoning, and agentic architectures. Rather than applying standard ML pipelines, you will work on training and shaping models that can reason over evidence, explore knowledge, and support scientific discovery. You will work closely with computational scientists and biologists to develop systems that integrate large-scale biomedical data, scientific literature, and experimental insights to support target discovery and disease understanding. This is an individual contributor role suited to a mid- to senior-level ML scientist who enjoys solving challenging applied research problems at the intersection of AI and biology. DAY TO DAY, YOU WILL * Design and develop agentic ML systems that can reason, plan, and interact with tools and data sources. * Train and refine LLM-based reasoning models using approaches such as reinforcement learning, RLHF, or other alignment techniques. * Develop algorithms that enable agents to explore and reason over complex scientific evidence. * Build systems that integrate large-scale biological data, knowledge sources, and scientific literature. * Collaborate closely with computational scientists, engineers, and biologists to translate scientific questions into ML systems. * Prototype and iterate on new approaches for reasoning, decision-making, and hypothesis generation in scientific domains. * Contribute to the technical direction of the team through experiments, publications, or new methodological ideas. We are particularly interested in candidates who have previously built systems such as: * Training reasoning or tool-using language models using RL, RLHF, or similar approaches * Developing agents that plan, explore, and interact with tools or environments * Designing learning loops where models improve through feedback or interaction * Building multi-step decision-making systems (e.g., scientific discovery systems, robotics policies, simulation agents, or planning systems) * Developing evaluation frameworks for reasoning or agentic models * Applying advanced ML techniques to complex real-world domains such as science, robotics, healthcare, or autonomous systems PROFESSIONALLY, YOU WILL HAVE * A PhD or MSc with substantial experience in Machine Learning, Computer Science, or a related quantitative field. * Strong experience working with large language models, including training, fine-tuning, or evaluation. * Experience with reinforcement learning, such as policy optimisation, actor–critic methods, or RLHF-style training pipelines. * Hands-on experience building agentic or decision-making systems (e.g., tool-using LLMs, planning agents, or multi-agent systems). * Strong programming skills in Python and modern ML frameworks. * Experience developing applied ML systems in complex domains. Bonus experience * Experience designing evaluation frameworks for reasoning or agentic systems. * Experience applying ML to scientific, biomedical, or healthcare problems. * Experience working in interdisciplinary environments combining ML and science. * Publications or open-source contributions related to LLMs, reinforcement learning, agentic systems, or applied AI. PERSONALLY, YOU * Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams. * Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work. * Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect. * Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams. * Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes. WORKING STYLE & CULTURE AT RELATION At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! RECRUITMENT AGENCIES Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. Relation is a committed equal opportunities employer.