AI Team LeadRobotics | Computer Vision | Embodied AIWe're working with one of Europe's most exciting robotics startups, building intelligent robotic systems that are already being deployed into real manufacturing environments.Following significant growth, they're looking for an experienced AI Team Lead to take ownership of a multidisciplinary AI function focused on computer vision, perception and machine learning for real-world robotics.You'll lead a team of around nine AI engineers while remaining close to the technology - reviewing code, making architectural decisions, mentoring engineers, and helping solve complex technical problems when needed. The team is highly technical, so credibility comes from your ability to lead by example as much as your management experience.What you'll be doingLeading, mentoring and developing a growing team of AI engineersDriving technical direction across perception, computer vision and machine learningConducting code reviews and providing technical guidance across the teamHiring, performance managing and coaching engineersWorking closely with robotics and software teams to deliver production-ready AI systemsDefining engineering standards, best practices and development processesSupporting the deployment of AI models onto real robotic hardwareHelping shape the long-term AI roadmap alongside senior engineering leadershipWe're looking for someone who hasPrevious experience leading an AI, Machine Learning or Computer Vision engineering teamA strong background in Computer Vision and deep learningExperience building production ML systems rather than purely research projectsStrong Python and PyTorch experienceExperience working with multimodal data and large-scale datasetsExposure to robotics, embedded systems or hardware-focused AI applicationsConfidence reviewing code and supporting engineers with technical challengesExperience hiring, mentoring and managing performance within engineering teamsBonus points forRobotics or embodied AI experience3D perception or sensor fusionROS2, Docker or KubernetesNVIDIA edge platformsSynthetic data or simulationCloud infrastructure and MLOps toolingWhy join?This is an opportunity to shape the AI capability of a rapidly growing robotics company solving genuinely difficult engineering problems.You'll join a business with real customers, production deployments and ambitious growth plans, working alongside an experienced leadership team with the autonomy to influence both technology and team direction.If you're an experienced technical leader who still enjoys getting into the code and wants to build AI that operates on real robots rather than prototypes, we'd love to hear from you.Interested? Apply now for a confidential discussion to learn more about the company, technology and opportunity.

We are looking for an experienced Data Engineer to join a growing data and AI team, helping to build modern data solutions that support advanced analytics and machine learning.This role centres on building robust data ingestion pipelines within Snowflake and delivering predictive analytics using Snowflake Cortex. While the majority of machine learning will leverage Snowflake's managed ML capabilities, there will also be opportunities to develop bespoke Python models where business requirements extend beyond native functionality.You will play a key role in designing scalable data engineering solutions, preparing high-quality datasets, and ensuring production-ready machine learning outputs are delivered to downstream applications.Key ResponsibilitiesDesign, build and maintain scalable data ingestion pipelines into Snowflake from structured and time-series data sources.Develop predictive analytics solutions using Snowflake Cortex, including forecasting, anomaly detection and classification.Prepare machine learning datasets through feature engineering, windowed aggregations and time-series transformations.Develop custom machine learning models using Python and Snowpark (including scikit-learn, XGBoost and LightGBM) where native Snowflake capabilities are not suitable.Integrate machine learning outputs into downstream applications and analytics platforms.Monitor and maintain production data pipelines and machine learning solutions, including data quality, model refreshes and performance monitoring.Optimise Snowflake performance and ensure data engineering best practices are followed.Required Skills & ExperienceStrong commercial experience with Snowflake, including SQL, Streams, Tasks, Snowpipe and performance optimisation.Experience using Snowflake Cortex ML capabilities for forecasting, anomaly detection and classification.Strong Python development skills, including Snowpark.Experience building data pipelines and preparing datasets for machine learning.Knowledge of time-series data processing and feature engineering techniques.Experience developing machine learning models using libraries such as scikit-learn, XGBoost or LightGBM.Understanding of production monitoring, data quality and model lifecycle management.Desirable ExperienceExperience with Snowflake ML features such as Model Registry and Feature Store.Knowledge of Azure Data Lake, Microsoft Fabric or other modern cloud data platforms.Familiarity with Snowflake AI capabilities such as AISQL, Cortex Search or related technologies.

Location: London (Hybrid - 3 days a week on site)Contract: Long-term ContractWe're recruiting for a leading global technology organisation seeking a Research Engineer to join a world-class AI research team working on large language models, AI agents and next-generation machine learning systems.ResponsibilitiesDesign, build and evaluate large-scale machine learning systems.Develop AI agents and LLM-based solutions using Python and PyTorch.Run experiments on large models and datasets.Collaborate with researchers and engineers to deliver cutting-edge AI solutions.Contribute high-quality, production-ready code in a fast-paced research environment.Required ExperienceStrong Python development skills.Hands-on experience with PyTorch or similar ML frameworks.Experience working with machine learning models at scale.Exposure to LLMs, Generative AI or AI agents.Bachelor's, Master's or PhD in Computer Science, Machine Learning, Mathematics, Physics or a related technical field.Strong problem-solving skills with the ability to execute in a research-driven environment.Nice to HavePhD or research-focused Master's.Experience in ML research, AI startups or leading technology companies.Experience with LLM post-training or agentic AI.What's on OfferOpportunity to work on cutting-edge AI research.Collaborate with some of the industry's leading researchers and engineers.Work on technology that will shape the future of AI.Long-term contract with a highly respected global technology organisation.

Principal Software Engineer (AI)Our work focuses on delivering innovative technology that creates meaningful, real-world impact. We are united by a shared commitment to developing solutions that help organisations harness the power of data, AI, and advanced software capabilities.We help life sciences and BioPharma organisations unlock the potential of AI and machine learning to improve outcomes and accelerate innovation. Through cloud-based software platforms and specialist services, we support organisations in managing complex scientific and operational data, improving workflows, and enabling smarter decision-making.With decades of expertise in scientific informatics, our solutions help organisations design, execute, and optimise processes, manage and structure data, and generate valuable insights across the product lifecycle—from research and development through to manufacturing.The Principal Software Engineer (AI) will provide technical leadership in the design and delivery of production-grade, GenAI-enabled capabilities across enterprise software platforms. The role focuses on applying large language models (LLMs) to real-world enterprise data, including scientific, clinical, and operational information, to enable AI-driven discoverability, summarisation, reporting, and decision support.Operating at principal level, you will be hands-on, guiding engineering teams through the transition from proof of concept (POC) to early adoption and general release, while helping establish sustainable AI engineering practices across the wider technology organisation.You will collaborate closely with data scientists, domain specialists, and technical teams to deliver intelligent solutions for knowledge extraction, decision support, and workflow automation.In this role, you will have the opportunity to:Lead the delivery of AI-enabled platform capabilities that accelerate insight generation and decision-making across complex enterprise environments.Design and productionise scalable GenAI solutions using approaches such as retrieval augmented generation (RAG), integration frameworks, and selectively applied agentic patterns—balancing capability, cost, performance, and trust.Translate scientific and business requirements into robust AI system designs that integrate effectively with data platforms, workflows, and APIs.Establish engineering best practices for GenAI and LLM applications, including architecture patterns, evaluation approaches, reliability, scalability, and maintainability standards across the AI engineering lifecycle.Act as a technical leader by mentoring engineers, influencing architectural decisions, and supporting successful delivery and adoption of AI capabilities across software platforms.Essential requirements:Experience designing, building, and operating LLM-powered capabilities such as document summarisation, retrieval augmented generation (RAG), and question-answering systems over enterprise datasets.Experience developing AI-ready data foundations, including unstructured data pipelines, metadata extraction and enrichment, and hybrid architectures using vector stores alongside relational databases.Proven ability to deploy AI systems into production environments, including monitoring model behaviour, data drift, cost, and latency.Strong judgment in making pragmatic engineering trade-offs to support reliability, scalability, and enterprise adoption.Experience establishing robust AI operational practices, including versioning of prompts, models, and data, as well as implementing feature flags and controlled rollout strategies.Ability to collaborate effectively with cross-functional partners, provide technical leadership, mentor engineers, and drive delivery in complex environments.Desirable (but not essential):Experience applying GenAI solutions within life sciences, healthcare, scientific, clinical, or regulated environments.Familiarity with building AI capabilities that support knowledge extraction, decision support, and workflow automation across enterprise data ecosystems.Experience with cloud-based platforms and modern data technologies such as Databricks and AWS.Experience defining or contributing to organisational best practices for AI engineering, including evaluation methods, governance frameworks, and scalable adoption approaches for generative and agentic AI.

Senior ASR Engineer (Speech Recognition / Voice AI)$200,000–250,000 equity benefitsRemote / San Francisco, CA (Hybrid)Full-time / PermanentDeepRec has partnered with a healthcare AI startup using conversational AI to reduce admin burden and improve patient experiences. Your work will sit at the centre of every interaction. When the speech system performs well, patients get faster support, clinicians receive better information, and healthcare teams spend less time on manual tasks.This role is for someone who enjoys solving real-world speech problems, not just improving benchmark scores.The OpportunityYou'll own ASR quality across live patient conversations. From noisy phone lines to accented speech and complex healthcare terminology, you'll identify failure patterns, build evaluation systems, and improve transcription performance where it matters most: production.You'll work across ASR, telephony, LLM workflows, and product teams to make every conversation more accurate and reliable.What You'll Do- Own ASR evaluation across live and recorded calls- Diagnose transcription failures and identify root causes- Build benchmarking frameworks and error analysis workflows- Improve recognition of healthcare language and terminology- Compare and evaluate ASR models and vendors- Create dashboards for quality monitoring and performance tracking- Partner with engineering and product teams on improvementsWhat You'll BringEssential- Strong experience with speech recognition or voice AI systems- Deep understanding of ASR evaluation and error analysis- Strong Python skills for ML and audio workflows- Experience diagnosing production AI system failuresDesirable- Experience adapting or fine-tuning ASR models- Background in healthcare, telephony, or regulated environments- Experience with real-time conversational AI systems*We encourage you to apply even if you don't meet every requirement. The right mindset matters as much as the right CV.*What's In It For You- Remote-first role across the US and Europe- Ownership of a business-critical AI capability- Work across ASR, telephony, LLMs, and healthcare AI- Healthcare, dental, vision, 401(k), and flexible paid time off- Opportunity to shape how conversational AI performs in production

Machine Learning Engineer, SpeechLLM Evaluations $250,000 - $350,000 bonus equity San Francisco, CA. Hybrid (3 days onsite)Full-time / PermanentDeepRec has partnered with a high-growth AI company building speech intelligence products used by more than 1.5 million people worldwide. This is a chance to define how their foundational Speech LLMs are measured, improved, and trusted. If you've ever felt model evaluation deserves the same attention as model training, you'll have the space to prove it here.The OpportunityYou'll join an early Speech LLM team where your work shapes research decisions, product quality, and model releases. You'll own the systems that answer one of the hardest questions in AI: how do you measure something as human as conversation, expression, and understanding?What You'll Do- Build evaluation frameworks for speech and conversational AI models- Define benchmarks for transcription, audio quality, and dialogue performance- Create automated evaluation pipelines for training checkpoints- Own dashboards that surface model health and regressions- Partner with researchers to translate capabilities into measurable outcomes- Investigate unexpected performance changes during model training- Improve evaluation speed, quality, and reliability across the research lifecycleWhat You'll BringEssential- Strong Python engineering experience in production environments- Experience building ML evaluation, data, or experimentation systems- Deep understanding of statistics, benchmarking, and model performance analysis- Ability to explain technical findings to varied audiencesDesirable- Experience with speech metrics such as WER, CER, PESQ, or MOS- Familiarity with LLM-as-a-Judge evaluation methods- Experience with ML observability tools such as Weights & Biases or MLflow*We encourage you to apply even if you don't meet every requirement. The right mindset matters as much as the right CV.*What's In It For You- Foundational role within a growing Speech LLM research team- Ownership of evaluation strategy and technical direction- Work on problems spanning ML, statistics, software, and research- Comprehensive healthcare, 401(k) matching, parental leave, and unlimited PTO- Conference, learning, and career development support- Direct influence on products used by a global customer base

AI Engineer:Contract/Freelance We're looking for an AI Engineer to help deliver the next generation of intelligent applications, combining LLMs, AI agents and modern cloud technologies to solve complex business challenges.Contract Details• Initial 6-month contract• Strong likelihood of extension beyond the initial engagement• Fully remote• Candidates must be based in Europe• Day rate: €300–€325 per day, depending on experienceThe RoleThis is a hands-on engineering role focused on building robust, scalable AI solutions rather than experimentation. You'll be designing agentic workflows, integrating AI into enterprise systems, and developing production-ready applications that make effective use of large language models and retrieval-based architectures.What You'll Bring:• Strong Python software engineering experience in production environments• Proven experience building applications with LLMs, including prompt design, tool usage, structured outputs and performance optimisation• Experience developing AI agents and orchestrating complex workflows• Knowledge of RAG architectures, vector search and contextual AI techniques• Experience integrating with APIs, enterprise platforms and cloud services• Understanding of AI reliability, evaluation, security and governance best practices• Experience with Azure AI technologies and Microsoft ecosystem integrations• Experience working with modern data pipelines and cloud-based data platforms• Ability to work closely with technical and business stakeholders to translate requirements into working solutionsDesirable:• Exposure to multimodal AI, computer vision or audio-based models• Knowledge of MLOps, model lifecycle management and deployment practices• Previous experience delivering AI solutions within people, talent or workforce-focused environmentsThis is an excellent opportunity for a contractor who enjoys building practical AI solutions, working with emerging technologies, and helping shape how organisations adopt intelligent systems at scale.

AI Engineer:Contract/Freelance We're looking for an AI Engineer to help deliver the next generation of intelligent applications, combining LLMs, AI agents and modern cloud technologies to solve complex business challenges.Contract Details• Initial 6-month contract• Strong likelihood of extension beyond the initial engagement• Fully remote• Candidates must be based in Europe• Day rate: €300–€325 per day, depending on experienceThe RoleThis is a hands-on engineering role focused on building robust, scalable AI solutions rather than experimentation. You'll be designing agentic workflows, integrating AI into enterprise systems, and developing production-ready applications that make effective use of large language models and retrieval-based architectures.What You'll Bring:• Strong Python software engineering experience in production environments• Proven experience building applications with LLMs, including prompt design, tool usage, structured outputs and performance optimisation• Experience developing AI agents and orchestrating complex workflows• Knowledge of RAG architectures, vector search and contextual AI techniques• Experience integrating with APIs, enterprise platforms and cloud services• Understanding of AI reliability, evaluation, security and governance best practices• Experience with Azure AI technologies and Microsoft ecosystem integrations• Experience working with modern data pipelines and cloud-based data platforms• Ability to work closely with technical and business stakeholders to translate requirements into working solutionsDesirable:• Exposure to multimodal AI, computer vision or audio-based models• Knowledge of MLOps, model lifecycle management and deployment practices• Previous experience delivering AI solutions within people, talent or workforce-focused environmentsThis is an excellent opportunity for a contractor who enjoys building practical AI solutions, working with emerging technologies, and helping shape how organisations adopt intelligent systems at scale.