HELLO,
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Lead AI Engineer Fully Remote - Europe I am working with a European health tech scale up that is building production grade AI systems used by insurers, governments, hospitals, and pharma groups to support complex drug pricing and reimbursement decisions.They are hiring a Lead AI Engineer to own the AI architecture end to end and drive how LLM based systems are designed, evaluated, and shipped into production.The role is hands on and strategic. You would lead AI initiatives across RAG pipelines, agent workflows, and tool orchestration, while mentoring a small engineering team and working closely with product and platform leads. A big focus is on building systems that are observable, cost aware, and reliable, not demos.The environment suits someone who has spent time taking LLM systems from concept to real usage, has strong Python and backend experience, and understands tradeoffs around latency, throughput, and evaluation. Experience with LangChain or LangGraph, FastAPI style services, cloud infrastructure, and MLOps practices is important.The product domain sits at the intersection of healthcare, pricing, and access to medicines, with real world impact and complex constraints. The team is senior, international, and remote first across Europe.If this sounds aligned with the kind of problems you enjoy working on, feel free to share your updated resume/cv!

Deep Learning Engineer – Advanced Robotics & VLM/VLALocation: Flexible / Remote (UK or Europe preferred) Employment Type: Full-timeAbout the CompanyOur client is an ambitious AI and robotics company developing next-generation humanoid systems designed to transform how intelligent automation supports industrial and everyday environments. Their mission is to advance human potential through robotics that are scalable, safe, and capable of performing complex real-world tasks. This is a rare opportunity to work at the intersection of deep learning, multimodal AI, and robotic embodiment, helping shape the foundations of a truly intelligent automation platform. The Role As a Deep Learning Engineer, you’ll design and train large-scale models that power robotic control and perception — from foundational representation learning to behaviour cloning and reinforcement learning. You’ll work across the full data-to-deployment lifecycle, experimenting with cutting-edge multimodal architectures and building robust pipelines for high-performance, real-time systems. Key ResponsibilitiesDevelop and train deep learning models for manipulation, navigation, and general policy learning.Collaborate with teleoperations and simulation teams to define data collection goals and bridge the sim-to-real gap.Train and fine-tune multimodal LLMs, VLMs, and VLAs, integrating diverse sensory modalities (vision, audio, proprioception, LiDAR, etc.).Build scalable data pipelines for continuous ingestion, curation, weak supervision, and retraining.Partner with MLOps and infrastructure teams to enable distributed training and optimize models for real-time deployment.Contribute to shaping the next generation of embodied AI systems for safe, efficient automation.About You3 years of experience building and deploying deep learning systems (industry or research).Strong proficiency in Python and PyTorch or JAX.Hands-on experience with LLMs, VLMs, or generative models for image/video.Deep understanding of training infrastructure (streaming datasets, checkpointing, distributed compute).Strong communicator with clear experiment documentation and the ability to explain complex technical decisions.Bonus PointsExperience in robotics, autonomous driving, or other embodied AI domains.Background in reinforcement learning (PPO, DPO, SAC, etc.) or RL for LLMs.Experience optimizing deep nets for production (latency, telemetry, on-device inference).Publications at top-tier ML conferences (ICLR, NeurIPS, ICML) or significant open-source contributions.Familiarity with OpenVLA, π models, or similar embodied AI frameworks.What’s on OfferCompetitive compensation including stock options.Flexible remote-first setup with opportunities for international collaboration.Work with world-class researchers and engineers building truly transformative technology.A fast-paced, innovation-driven culture where ideas move quickly from concept to prototype.

Lead Speech Research Scientist (ASR/TTS) London preferred | Remote considered | Visa sponsorship availableWe’re collaborating with a growing AI company developing advanced conversational technologies that power intelligent voice and chat systems for global enterprises. This is a senior research and leadership role for someone with deep expertise in ASR, TTS, and related speech–language technologies. You’ll head a high-impact research group, working directly with company leadership to define research priorities, guide technical direction, and translate innovations into production.Key Responsibilities:Lead applied research and development in speech recognition, speech synthesis, and conversational AI.Define the research roadmap and ensure alignment with strategic and product goals.Mentor and grow a team of researchers, fostering collaboration and innovation.Translate real-world product challenges into clear research objectives and milestones.Oversee data strategy, evaluation metrics, and system performance.Collaborate closely with product and engineering teams to deploy research outcomes.Represent the team externally through papers, conferences, and community engagement.What We’re Looking ForPhD (preferred) or Master’s in Speech Technology, Computer Science, or related field.Proven expertise in Automatic Speech Recognition (ASR) and/or Text-to-Speech (TTS).3 years of applied research experience in speech or language AI (industry or academic).2 years leading or mentoring research teams or projects.Strong programming skills in Python, with deep learning experience using PyTorch.Practical experience taking models from research to production environments.Bonus SkillsExperience with multilingual or low-resource speech systems.Familiarity with LLM integration into conversational pipelines.Strong engineering foundations (Git, Docker, CI/CD).Publications in major speech or AI conferences (e.g., Interspeech, ICASSP, NeurIPS).This is a key hire in a company entering an exciting growth phase — an opportunity to shape the future of speech and conversational AI while leading a talented, expanding research team.