Lead ML Research Scientist

Lead cutting-edge AI research for real-world engineering systems.Shape strategy, publish research, and build a high-impact team. About Our Client Our Client is a deep-tech AI company building domain-specific AI systems for industries such as semiconductors, automotive, telecom, aerospace, defence, and industrial IoT. The company develops sovereign, deployable AI models and platforms designed for complex engineering environments where accuracy, security, and domain expertise are critical. Backed by leading investors and supported through strategic technology partnerships, the Client is focused on transforming engineering workflows through specialized AI innovation. Job Description Define and lead the company's machine learning research agenda across model training, reinforcement learning, synthetic data, and neurosymbolic AI.Own the end-to-end model development lifecycle, including pre-training, fine-tuning, alignment, and evaluation.Establish high research standards around experimentation, reproducibility, and evaluation methodologies.Build, mentor, and guide a team of AI researchers and engineers.Lead research on reinforcement learning using real hardware feedback and deployment data.Drive innovation in synthetic data generation to improve model performance on domain-specific tasks.Explore and develop approaches that combine neural models with formal verification and symbolic reasoning techniques.Collaborate closely with engineering teams to translate research breakthroughs into production systems.Monitor advancements in AI research and contribute to the company's external technical presence through publications and industry engagement. The Successful Applicant A successful Lead ML Researcher should have: PhD in Machine Learning, NLP, or a related field, or equivalent depth of research experience in industry.6+ years of hands-on ML research experience with proven production impact.Strong experience training, fine-tuning, and evaluating large language models at scale.Deep understanding of transformer architectures, optimization techniques, and LLM training methodologies.Demonstrated experience leading research programs and mentoring technical teams.Strong experimental and analytical skills, with the ability to turn research into measurable outcomes.Research publications at top-tier venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, or similar forums are highly valued.Experience with areas such as RLHF/RLAIF, formal methods, program verification, synthetic data generation, or embedded systems is a strong advantage. What's on Offer Competitive salary and early-stage equity opportunity.Opportunity to own and influence the company's long-term AI research direction.Direct collaboration with founders, AI researchers, and engineering leaders.Dedicated compute resources to support ambitious research initiatives.Opportunities and support for publishing non-proprietary research.Work on cutting-edge AI challenges in high-impact engineering and industrial domains. Lead cutting-edge AI research for real-world engineering systems.Shape strategy, publish research, and build a high-impact team. About Our Client Our Client is a deep-tech AI company building domain-specific AI systems for industries such as semiconductors, automotive, telecom, aerospace, defence, and industrial IoT. The company develops sovereign, deployable AI models and platforms designed for complex engineering environments where accuracy, security, and domain expertise are critical. Backed by leading investors and supported through strategic technology partnerships, the Client is focused on transforming engineering workflows through specialized AI innovation. Job Description Define and lead the company's machine learning research agenda across model training, reinforcement learning, synthetic data, and neurosymbolic AI.Own the end-to-end model development lifecycle, including pre-training, fine-tuning, alignment, and evaluation.Establish high research standards around experimentation, reproducibility, and evaluation methodologies.Build, mentor, and guide a team of AI researchers and engineers.Lead research on reinforcement learning using real hardware feedback and deployment data.Drive innovation in synthetic data generation to improve model performance on domain-specific tasks.Explore and develop approaches that combine neural models with formal verification and symbolic reasoning techniques.Collaborate closely with engineering teams to translate research breakthroughs into production systems.Monitor advancements in AI research and contribute to the company's external technical presence through publications and industry engagement. The Successful Applicant A successful Lead ML Researcher should have: PhD in Machine Learning, NLP, or a related field, or equivalent depth of research experience in industry.6+ years of hands-on ML research experience with proven production impact.Strong experience training, fine-tuning, and eva