Research Engineer, Scalable ML Workflows

Jobtailor; Paris; Sur place; EUR 70 000 - 100 000; Plein temps

Résumé du poste

Jobtailor is seeking an experienced ML Engineer to translate real customer requirements into reliable training and deployment workflows, spanning model adaptation, post-training evaluation, data pipelines, and infrastructure.

You will build and improve post-training and evaluation workflows for CPT, SFT, RL, and distillation, develop tools for synthetic data generation, debugging, observability, and scalable systems across cloud and on‑prem environments.

Qualifications

• Experience with large codebases, testing, CI, and deployment ownership.
• Hands-on experience with LLM training or post-training pipelines.
• Ability to debug distributed ML jobs and data issues.
• Strong communication with technical and non-technical stakeholders.
• Experience building ML infrastructure and data pipelines.

Responsabilités

• Turn real customer requirements into reliable training and deployment workflows
• Work end-to-end across model adaptation and post-training, evaluation, data, and infrastructure
• Build and improve post-training and evaluation workflows for CPT, SFT, RL, and distillation
• Develop tools and pipelines for synthetic data generation, data curation, training, evaluation, and deployment
• Debug and harden large-scale ML systems, including distributed training, scheduling/execution, checkpointing, observability, and reproducibility
• Improve the Forge codebase through clear APIs, tests, documentation, and maintainable abstractions
• Advance the RL training stack, including high-throughput asynchronous rollout and scalable post-training systems
• Ensure Forge deployment is seamless and adaptable across diverse clients, hardware, software stacks, cloud, and on-premises environments
• Partner with researchers and infrastructure engineers to translate bottlenecks into concrete system improvements
• Collaborate with scientists, engineers, product, and customer-facing teams to ship maintainable and trusted Forge projects

Connaissances

Python Engineering

PyTorch

JAX

Distributed Systems

Data Pipelines

Testing & CI

Operational Ownership

Clear Communication

Outils

FSDP

DeepSpeed

Megatron

SLURM

Ray

Kubernetes

Kueue

Karpenter

Skypilot

Description du poste

Jobtailor is seeking an experienced ML Engineer to translate real customer requirements into reliable training and deployment workflows, spanning model adaptation, post-training evaluation, data pipelines, and infrastructure.

You will build and improve post-training and evaluation workflows for CPT, SFT, RL, and distillation, develop tools for synthetic data generation, debugging, observability, and scalable systems across cloud and on‑prem environments.