Lead research on hyper-personalization and memory evolution for AI agents, developing algorithms, models, and prototypes to enhance user understanding and personalization across tasks.
Responsibilities
Conduct research on long-term memory and personalization modeling
Develop and evaluate multi-modal interaction trajectories and skill learning
Design and implement multi-agent collaborative memory systems
Adapt large models for personalization and memory read/write
Create high-quality training data and conduct supervised fine-tuning
Requirements
Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics or related field
Lead research and development of large language models and reinforcement learning systems at SpaceXSI, driving end‑to‑end experiments and scaling studies.
Compensation
Annual Salary:
$220,000 - $357,000 USD
Responsibilities
Design and run rigorous experiments that turn research ideas into measurable gains in model capability
Improve data recipes through data quality, deduplication, and mixture experiments
Define what makes RL data and rewards good, including grader design and preventing reward hacking
Advance training science, from architecture and scaling experiments to post‑training recipes for coding and computer‑use agents
Build evals and targeted tasks that expose model weaknesses and guide where the team invests next
Requirements
MS or PhD in CS, ML, math, physics or a related field, or equivalent research experience
Lead and develop the transactional finance team, owning AP/AR operations across the ELEMIS group, driving automation, process improvement and financial controls.
Responsibilities
Lead, mentor and develop the team
Own all transactional finance operations across the group
Build a strong, proportionate control environment
Improve working capital by managing DSO, DPO and reducing aged debt
Collaborate cross-functionally to integrate financial processes
Apply AI engineering expertise to deploy, optimize, and scale models for strategic customers, leading technical journeys from POCs to production endpoints.
Responsibilities
Scope workloads, define metrics (TTFT, throughput, cost/token), build benchmarks, and lead technical POCs.
Serve as the technical lead for customer engineering teams through architecture reviews and rollout planning.
Tune engines (KV cache, speculative decoding, parallelism, quantization) to hit aggressive performance targets.
Profile and diagnose bottlenecks at the engine level to deliver production fixes.
Own end-to-end customer onboarding, deployment, autoscaling, capacity planning, and SLO monitoring.
Consultant spécialisé en protection des données et conformité RGPD, intervenant auprès de clients grands comptes pour audit, cartographie, gouvernance, sensibilisation et développement d'offres de conseil.
Responsibilities
Audit de conformité RGPD
Cartographie des traitements et mise à jour du registre
Réalisation d'analyses d'impact sur la protection des données
Animation de formations et ateliers de sensibilisation
Définition de méthodologies industrielles et création de check-lists
Requirements
BAC+5 en école de commerce, d'ingénieur ou master universitaire en droit du numérique / conformité
Internship focused on developing on-device long‑term memory for automotive agents using multimodal small language models.
Responsibilities
Design and implement multimodal long‑term memory (RAG) for automotive agents in resource‑constrained in‑vehicle environments.
Fine‑tune LFM3 models, especially LFM3‑Omni‑2B, and other small language models for memory, preference extraction, and function calling (SFT, LoRA/QLoRA).
Apply reinforcement learning (e.g., DPO, GRPO) to improve memory, activation, and tool‑use decisions.
Build trigger‑based activation from multimodal cabin and vehicle signals, using decision models (e.g., LFM3 d1‑omni‑2B) and lightweight classifiers.
Build classifiers for turn detection, PII detection, and intent routing.