Research Engineer

Bigblue

📍 Paris | Full-time | Fluent 🇫🇷 & 🇬🇧   At Bigblue, we're building the logistics backbone for the next generation of commerce. Modern brands sell everywhere: through their own online stores, marketplaces, retail, social commerce, and more. Across every channel, customers expect the same fast, reliable, and transparent experience after they buy. What used to be Amazon's exclusive advantage is now becoming the standard for every ambitious brand. We're helping them get there. Since 2018, we've built a tech-driven fulfilment platform used by 600+ brands, including Muji, Aigle, Scuffers, and Cabaïa. With 200+ Bigbluers across the UK, France, Spain, and Germany, our proprietary tech stack, and a network of 9 warehouses and over 100,000 sqm of fulfilment space across Europe, we ship millions of orders every month. And we're nowhere near done! Backed by €20M+ in funding, we're expanding across Europe and building the operating system that will power modern commerce operations at a global scale. At Bigblue, we hold ourselves to a very high bar: in the quality of our product, the rigour of our operations, and the care we bring to every merchant we work with. You'll be working alongside talented people on real, high-impact problems, in an environment where high standards come with genuine support, ownership, and room to grow. If you want your work to matter from day one, you're in the right place.     The Role   As an Applied Scientist, you will develop and maintain efficient and robust algorithms that significantly improve our warehouse operations. You'll work at the intersection of research and engineering, identifying optimization opportunities, collaborating with stakeholders on operational feasibility, and shipping solutions that have immediate, visible impact on our European fulfillment network.   This is probably one of the highest-leverage job openings we have today – each percentage of performance we squeeze out of our algorithms allow us to scale even faster.   What You Will Work On Identify optimization opportunities across our WMS algorithms Align with stakeholders on operational feasibility and discuss tradeoffs Develop and maintain efficient and robust algorithms that significantly improve our operations Collect feedback, measure performance and iterate based on real-world results

Datadog

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production.   Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.   We are focused on two research areas:   1. World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. 2. Trained Agents for Observability-- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.   What You'll Do:   * Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling * Implement models, run experiments at scale, and profile for reliability, performance, and cost * Build simulation environments and replay infrastructure for agent training and evaluation * Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery * Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity * Collaborate with Research Scientists, Product, and Engineering to integrate capabilities into Datadog's products and to harden prototypes into reliable services * Contribute to research publications at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and produce high-quality code, documentation, and open-source artifacts Who You Are:   * You have depth in distributed computing, RL Infra, and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus * You are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and comfortable with modern cloud and data infrastructure * You have practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU acceleration * You have practical experience with large-scale model training and fine-tuning, including frameworks like Megatron-LM, DeepSpeed, SkyRL, VeRL, or TorchTitan, and techniques such as SFT, RLVR, RLHF, and efficient inference (quantization, speculative decoding) * You can explain design and performance trade-offs clearly to both technical and non-technical audiences * You have experience supporting or contributing to research publications   Bonus Points (any of the following):   * You have strong software engineering skills with experience in domains such as observability, SRE, or security * You have experience bridging research prototypes and real-world product applications, especially with large foundation models, world models, or RL-trained agents * You have a passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment * You have hands-on experience with GPU programming and optimization, including CUDA * You have experience writing production data pipelines and applications * You have experience building simulation or sandbox environments for agent training   Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.   Benefits and Growth: * Competitive global benefits  * New hire stock equity (RSUs) and employee stock purchase plan (ESPP) * Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris * Opportunity to attend and present at conferences and meetups * Intra-departmental mentor and buddy program for in-house networking * An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)   Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.   About Datadog:  Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.   Equal Opportunity at Datadog: Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.   Your Privacy: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice.   #LI-hybrid ---------------------------------------------------------------------------------------------------------------------------------- About Datadog:  Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. ---------------------------------------------------------------------------------------------------------------------------------- Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.  Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.  Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

Harmattan AI

ABOUT US Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. ABOUT THE ROLE Harmattan AI is heavily pushing the boundaries of autonomous systems, where the perception of the surrounding world through visual cues is a vital component. To make sense of incoming visual data and enable mission-critical downstream decisions, we have developed custom detection models. As our product and project portfolio expands, we are diversifying our efforts in this space across multiple embedded platforms. As an ML Research Engineer in the Detect&Track Distillation team, you will join us at a very early stage, giving you a unique opportunity to heavily influence the technical direction of the team. Operating out of Lausanne, Paris, or Zurich, you will focus on taking large foundation models and distilling them into highly optimized, task-specific components. Your work will span target detection, classification, and target re-identification across time, directly tackling the hardware inference constraints of diverse edge and embedded systems. RESPONSIBILITIES * Model Distillation & Finetuning: Take large foundation models and compress/distill them into highly specific, efficient components optimized for smaller tasks and target detection. * Edge AI Optimization: Optimize neural networks for constrained embedded systems using techniques such as quantization (PTQ vs. QAT), pruning, and LoRA. * Pipeline Management & MLOps: Build, heavily modify, and manage training, evaluation, and MLOps pipelines while ensuring reproducibility, robust logging, and version control. * Data Curation: Collaborate on data curation and the creation of task-specific datasets to constantly improve model accuracy. * Benchmarking & Evaluation: Framework-level benchmarking of newly distilled models to evaluate performance and latency, ensuring results are fully aligned with real-world operational deployments. * Research & Innovation: Stay at the absolute forefront of scientific trends in computer vision and quantization research to introduce cutting-edge methodologies to the team. * Cross-Functional Collaboration: Work closely with the Detect&Track Foundation team, downstream System Engineers, Project Teams, and Mission Intelligence to deliver robust solutions. * Mentorship: Depending on seniority, support the team by managing or mentoring junior engineers. CANDIDATE REQUIREMENTS * Educational Background: A strong academic record with a degree in a STEM field (e.g., Computer Science, Engineering, Mathematics). * Deep Learning & Computer Vision: Proven experience running vision neural networks, developing target detection architectures, or managing re-identification tasks. * Model Compression & Edge AI: Hands-on expertise in knowledge distillation, model compression, and deploying networks onto highly constrained embedded systems or edge hardware (e.g., Jetson, custom NPUs, wearables). * Technical Competence & Infrastructure: Proficiency in MLOps, GPU compute, and building infrastructure (such as training pipeline templates and loggers). * Professional Attributes: * Highly structured, analytical, task-aligned, and research-oriented. * Excellent communication and influence skills, with the ability to effectively translate and present complex benchmarking data to downstream users and senior stakeholders. * Thrives under pressure in a fast-paced environment with a “no-task-is-too-small” mentality toward building foundational team infrastructure. * Commitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.