Location: Remote (Soundsense AI is remote-first)Job Type: ContractLength: 3-6 monthsRate: Competitive day rateHours: 2-3 days a week (more possible if desired) We are seeking a Senior AI Engineer to lead the scoping, building, and deployment of custom AI solutions with our key clients. This role involves embedding with client teams to transform their operational challenges into production-ready AI systems, ensuring rapid delivery and measurable real-world impact. You will act as the technical and consultative bridge between our clients and the core SoundSense AI product and engineering teams. What Makes This Role Unique: You’ll be joining an elite, senior team working directly on building production AI systems for diverse client needs. This is a highly hands-on role where you’ll define the solution and write the code to make it real. You'll enjoy significant autonomy and will be directly involved in shaping client outcomes and our own product direction. We are a remote-first company that offers flexible hours and an environment where high-impact work is the standard. Our Team: Example Projects You'd Work On: Build an AI to analyse laboratory results, extract and translate the data to a standardised format alongside concluding commentary on the results Build an AI to summarise the state of a customer account for a car finance business (calls, emails, payments, loan details, previous CRM actions etc) to understand current state and give the next best action to maximise recovery processes Build an AI to automatically book or reschedule a engineering appointments for building maintenance services Core Responsibilities: Client Scoping and Solution Design: Work closely with clients to deeply understand complex business problems, define clear problem statements, and translate requirements into a technical AI solution roadmap. End-to-End System Development: Architect, build, and deploy custom full-stack AI/ML applications and integrations, from data ingestion to the final user-facing system. Production Deployment: Implement, configure, and manage SOTA AI models into client production environments (cloud, on-premise, or hybrid), ensuring security, scalability, and performance. Technical Enablement: Develop robust documentation and lead technical workshops to enable client engineering teams to own, operate, and maintain the deployed solutions post-launch. Cross-Functional Collaboration: Partner with client engineering teams and internal Product/R&D teams to identify product gaps, capture field feedback, and influence our core technology roadmap. System Optimisation: Implement rigorous monitoring, testing, and performance tuning to ensure the deployed AI solution delivers continuous value and meets defined technical and business KPIs. About You: 🎯 Key Requirements 3+ Years experience building and deploying enterprise-grade software systems at top-tier organisations. Full-Stack Proficiency: Expert in modern backend development (e.g., high-level language proficiency), API development, containerised deployment patterns, data pipelines, and cloud platforms (AWS/GCP/Azure). Coding Agent Proficiency: Experience or strong proficiency working with coding agents (e.g., GitHub Copilot, internal tools) to maximise development speed and quality. LLM System Architecture: Deep understanding of the architecture, development cycles, and MLOps required to build and scale reliable LLM applications. Product-Driven Execution: Strong product sense with the ability to rapidly prototype, iterate, and ship solutions that prioritize customer outcomes. Execution & Autonomy: Proven ability to manage concurrent projects, take ownership, and operate as an independent self-starter (a "ship fast, improve fast" mentality). Prompt Engineering & Evaluation: Willingness to be hands-on with advanced prompt engineering and the development of robust LLM evaluation systems. Stakeholder Management: Excellent communication skills and comfort with significant client/stakeholder interaction. Availability: Must be available during core collaboration hours (9am - 1pm GMT). ✨ Bonus Points Experience with advanced LLM architectures (RAG, Agentic Systems, etc.). Hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex). Production experience setting up evaluation systems and metrics. ❌ This Role Is NOT For Junior Developers seeking on-the-job AI/ML training. Engineers who prefer minimal client interaction. Those requiring detailed task specifications and constant direction. Perfectionists who prioritise technical elegance over delivery speed. Work Terms: Location: Remote (Soundsense AI is remote-first) Job Type: Contract Length: 3-6 months Rate: Competitive day rate Hours: 2-3 days a week Apply

Location: RemoteJob Type: Contract We are seeking a highly skilled and experienced contract data scientist to lead the development of a cutting-edge AI prioritisation model for a debt collections process. This critical role involves transforming our collections process into a data-driven, strategic operation by intelligently prioritising daily arrears worklists, ultimately empowering our agents, improving cash flow, and reducing arrears. What Makes This Role Unique: You’ll be joining a small, senior team working directly with an experienced and hands-on CTO and product leader. We move fast, operate lean, and collaborate closely. You’ll have a lot of autonomy, the chance to work on meaty problems, and be directly involved in shaping real product decisions. This is high-impact work with real-world consequences — helping SMEs, many of whom are still miles behind on AI adoption, make a leap forward. Core Responsibilities: Build, train, and validate a machine learning model using historical data to ensure predictive accuracy. Collaborate with technical teams to define and build the data exchange process, including developing a production API to deliver the prioritised worklist. Deploy the backend scoring engine into a secure production environment, addressing data residency and regulatory requirements. Implement robust monitoring and reporting to track model performance, prevent silent failures, and ensure outputs are based on the freshest available data. Analyze the performance of the live system against defined KPIs and synthesise findings into a final report. Provide data-driven recommendations and a clear strategic pathway for the next version of the solution. Required Skills: Proven experience in developing, training, and validating machine learning models. Expertise in data discovery and data flow design. Skilled in constructing data engineering pipelines. Proficiency in implementing monitoring and reporting to track model performance. Experience in analysing KPI data and contributing to strategic roadmaps. Experience in collaborative design of solution architecture and API specifications. Strong communication skills to work effectively with both technical and business teams during workshops, testing, and go-live phases. Work Terms: Project Length: 16 weeks Weekly Commitment: 4 days Rate: Competitive daily rate Location: Remote/On-site flexibility Apply