Phd Position F/m Embedded Machine Learning Programming

Le descriptif de l’offre ci-dessous est en Anglais_ **Type de contrat**: CDD **Niveau de diplôme exigé**: Bac + 5 ou équivalent **Fonction**: Doctorant **Contexte et atouts du poste**: **Scientific context**: - )batches allowing the efficient scheduling of computations and I/O, parameter updates, etc. The same applies to reinforcement learning (RL) agents. Back to the automated driving example, stateful behavior is essential to taking into account previously-inferred facts such as speed limits, whether the current lane is a left turn etc., long after the acquisition of sensor inputs. Other examples of ML components embedded into stateful reactive feedback loops include model-predictive maintenance, control, and digital twins. ML models themselves involve stateful constructs in the form of recurrent neural network (RNN) layers. When generating optimized code, even matrix products and convolutions in feedforward networks can be folded over time, using (stateful) buffering to reduce memory footprint. In distributed settings, the efficient implementation of large models involves pipelined communications and computations, which amounts to locally recovering a streaming execution pattern. Considering this broad range of scenarios, we observe that existing ML frameworks inadequately capture reactive aspects, raising barriers between differentiable models and the associated control, optimization, and input/output code. These barriers worsen the gap between ML research and system capabilities, particularly in the area of control automation where embedded ML engineering relies on undisclosed, ad-hoc implementations. **Mission confiée**: The objective of this PhD is to advance on either, or both the MLR language design and the MLR compilation fronts. - On the language design (syntax and semantics) side, of particular interest is the introduction of iterators allowing for seamless conversion of iterations performed in time, on streams, into iterations performed in space, on tensors. Such transformations are needed both at high level, e.g. to introduce a "batch" dimension into a computation, and at low level, e.g. to specify how a large tensorial operation is decomposed for execution onto hardware. - On the compilation side, the key difficulty is the handling of bidirectional recurrences. Classical reactive formalisms such as Lustre can be compiled into very efficient, statically-scheduled code running in constant memory, without buffering. By comparison, the ML-specific bidirectional recurrences implicitly require buffering and dynamic scheduling (like the tape-based methods used during training). Replacing this implicit buffering with explicit, efficient and bounded buffering under a mostly-static scheduling has the potential to largely improve the performance and predictibility of generated code. The internship will involve regular interactions with: - Google DeepMind for the language design and compilation work. - Our automotive partners (the ASTRA team and Valeo) for the evaluation of MLR on the AD use case. **Principales activités**: Main activities: - State of the art analysis - Use case modeling and evaluation - Proposal of language extensions and compilation methods - Research paper writing **Compétences**: Languages : Proficiency in either French or English is required. **Avantages**: - Subsidized meals - Partial reimbursement of public transport costs - Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) - Possibility of teleworking - Professional equipment available (videoconferencing, loan of computer equipment, etc.) - Social, cultural and sports events and activities - Access to vocational training - Social security coverage **Informations générales**: - **Ville**: Paris - **Centre Inria**: Centre Inria de Paris - **Date de prise de fonction souhaitée**: 2025-10-01 - **Durée de contrat**: 3 ans - **Date limite pour postuler**: 2025-09-06 **Consignes pour postuler**: **Sécurité défense**: Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement. **Politique de recrutement**: Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap. **Contacts**: - **Équipe Inria**: AT-PRO AE - **Directeur de thèse**: **L'essentiel pour réussir**: We are seeking a student that is highly motivated to do research at the intersection of Machine Learning, programming languages, and embedde