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ai engineer

eSense

<div>
 Position Overview
 
 
 
 
 Mid-Level AI Engineer with strong hands-on experience in end-to-end AI system development, specializing in on-premises and private cloud AI deployments. This role focuses on building production-grade AI solutions using primarily local models, optimizing GPU-based training and fine-tuning pipelines, and developing scalable RAG, agentic, multimodal, and speech-enabled systems.
 
 
 
 
 Key Responsibilities&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Analyze requirements and contribute to technical AI solution design.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Strong programming skills in Python (mandatory).
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience in backend development (APIs, microservices, model serving).
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Hands-on experience with local LLM deployment and optimization.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience in RAG system design and vector databases.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Practical experience in model fine-tuning (LoRA / PEFT).
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Solid understanding of: Transformer architecture, quantization techniques, and embeddings with retrieval.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience working in Linux environments.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Participate in peer code reviews and team planning activities.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Provide task estimations and deliver within approved timelines.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Apply secure coding practices and participate in bug resolution with quality metrics in mind.
 
 
 
 
 Qualifications
 
 
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Bachelor&rsquo;s degree in computer science, Artificial Intelligence, Data Science, or related discipline.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;2-5 years of experience in AI Engineering.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Proficiency in C#, .NET Core and Python.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with Structured and Unstructured databases.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with Angular or other frontend technologies is a strong plus.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Working knowledge of relational databases (i.e., SQL Server) and non-relational databases (i.e., Qdrant)
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Familiarity with Git, RESTful services, and Agile development methodologies
 
</div>

AI Engineer

FlairsTech

<div>
 
 
 About the Role
 
 
 
 
 
 
 We are hiring an elite cohort of highly hands-on AI Engineers to embed directly within Valsoft's Edelweiss Software Group portfolio of vertical market B2B SaaS companies.
 
 
 We are looking for builders &mdash; engineers who operate as system orchestrators rather than traditional syntax typists. You will design, implement, and deploy secure, enterprise-grade AI systems that automate workflows, eliminate manual processes, rapidly modernize massive legacy codebases, and create measurable business impact.
 
 
 You will work directly with operators, product teams, and leadership to turn inefficiencies into intelligent systems. Operating with a distinct startup mindset within a large-scale corporate portfolio, your primary focus is driving rapid product innovation, executing AI-driven legacy modernization via agentic swarm coding, and maximizing ROI through autonomous multi-agent workflows.
 
 
 If you enjoy owning problems end-to-end, possess a relentless bias toward action, and thrive on shipping real systems into production at an unprecedented velocity, this role is for you.
 
 
 Your mission: act as an organizational force multiplier to increase efficiency, reduce CAC payback periods, increase Net Revenue Retention (NRR), and unlock massive scalability.
 
 
 What You&rsquo;ll Do
 
 
 Build &amp; Ship AI Systems
 
 <ul>
 <li>
 Design, develop, and deploy production-grade, secure AI systems utilizing scalable polyglot microservices.
 </li>
 <li>
 Integrate state-of-the-art enterprise LLMs (Anthropic Claude Opus 4.6, OpenAI GPT-5.2, Google Gemini 3) into SaaS platforms via dynamic, fault-tolerant API routing gateways.
 </li>
 <li>
 Modernize extensive codebases using agentic swarm coding, automated refactoring tools, and cross-language translation.
 </li>
 <li>
 Develop autonomous multi-agent workflows utilizing parallel orchestration tools like the OpenAI Codex and Claude Code CLI.
 </li>
 <li>
 Automate comprehensive technical documentation for legacy and newly generated codebases using AI orchestration.
 </li>
 <li>
 Rapidly prototype &rarr; validate via adversarial testing &rarr; deploy &rarr; iterate.
 </li>
 </ul>
 
 Architect AI Infrastructure
 
 <ul>
 <li>
 Apply good knowledge of software engineering design patterns and architecture to ensure the scalability and maintainability of AI-generated systems.
 </li>
 <li>
 Implement complex RAG systems and continually optimize trade-offs between massive-context hydration (up to 1-million tokens) and multi-stage semantic retrieval.
 </li>
 <li>
 Work extensively with vector databases (Pinecone, Weaviate, FAISS) and manage persistent document embedding queues.
 </li>
 <li>
 Build polyglot microservices specifically capable of handling massive, long-running operational tasks and streaming continuous token generation via persistent connection protocols (WebSockets and Server-Sent Events).
 </li>
 <li>
 Ensure SOC2 compliance, data residency (via inference_geo parameters), and deterministic execution through policy-as-code agentic governance.
 </li>
 <li>
 Deploy and scale models strictly within secure managed cloud boundaries (Azure AI, AWS Bedrock, GCP Vertex) leveraging Docker and Kubernetes orchestration.
 </li>
 </ul>
 
 Transform the Application Lifecycle &amp; Collaborate
 
 <ul>
 <li>
 Architect "zero-touch deployment" CI/CD pipelines fortified with adversarial gating.
 </li>
 <li>
 Design and implement unit test and benchmark automation workflows, utilizing AI agentic coding to rigorously validate and test produced code.
 </li>
 <li>
 Natively integrate synthetic red teaming into CI/CD to actively prevent prompt drift, reward hacking, and logic degradation.
 </li>
 <li>
 Work directly with non-technical stakeholders to translate ambiguous business problems into secure, scalable AI solutions.
 </li>
 <li>
 Optimize Atlassian workflows (Jira) to automate the translation of unstructured product requirements into structured prompt contexts for AI agents.
 </li>
 </ul>
 
 Required Technical Skills
 
 
 Core Engineering
 
 <ul>
 <li>
 5+ years of demonstrable enterprise software development experience.
 </li>
 <li>
 Good knowledge of software engineering design patterns and architecture.
 </li>
 <li>
 Flexible in most popular programming languages (Python, Javascript, Typescript, .Net, C#) and web frameworks (NextJS, etc.).
 </li>
 <li>
 Ability to switch environments and programming using agentic programming tools to validate and test your produced code.
 </li>
 <li>
 Backend development experience designing polyglot APIs, decoupled asynchronous microservices, and utilizing persistent connection protocols (WebSockets/SSE).
 </li>
 <li>
 Familiarity with containerization (Docker, Kubernetes) and architecting multi-region, fault-tolerant cloud infrastructure (AWS, Azure, or GCP).
 </li>
 </ul>
 
 AI &amp; ML Systems
 
 <ul>
 <li>
 Enterprise LLM integration and dynamic API routing (OpenAI, Anthropic, Gemini, DeepSeek).
 </li>
 <li>
 Multi-agent orchestration and advanced CLI tooling (Claude Code with Auto Hot-Reload and Forking Context, OpenAI Codex).
 </li>
 <li>
 Mastery of localized AI IDE layers (Cursor for repository-wide reasoning, GitHub Copilot).
 </li>
 <li>
 Massive-context RAG pipelines, dynamic chunking strategies, and vector databases (Pinecone, Weaviate, FAISS).
 </li>
 <li>
 Custom evaluations (LangSmith), structured outputs, and managed fine-tuning in secure cloud boundaries.
 </li>
 </ul>
 
 MLOps &amp; Process Automation
 
 <ul>
 <li>
 Zero-touch CI/CD pipelines and advanced Git workflows (including Git worktree isolation for autonomous sub-agents).
 </li>
 <li>
 Unit test and benchmark automation frameworks fully integrated with AI-driven testing.
 </li>
 <li>
 Adversarial LLM testing and automated synthetic red-teaming integration.
 </li>
 <li>
 Monitoring dynamic access limits and real-time atomic token/credit consumption tracking.
 </li>
 <li>
 Strict hallucination mitigation, enterprise guardrails, and deterministic policy-as-code execution.
 </li>
 </ul>
 
 Profile We&rsquo;re Looking For
 
 <ul>
 <li>
 Highly hands-on &mdash; you ship, not just design. You operate at an unprecedented velocity by orchestrating advanced autonomous tools.
 </li>
 <li>
 Entrepreneurial startup mindset &mdash; you see legacy inefficiencies and act with a relentless bias toward rapid action.
 </li>
 <li>
 Comfortable with ambiguity and translating complex business needs into precise technical execution.
 </li>
 <li>
 Business-oriented &mdash; you care deeply about ROI, operational leverage, and driving specific financial metrics (CAC, NRR).
 </li>
 <li>
 Fast learner &mdash; keeps up with real-time shifts in AI ecosystems, hardware architectures (e.g., Cerebras chips), and vital API migrations.
 </li>
 <li>
 Pragmatic &mdash; uses the right secure enterprise tool for the specific bottleneck, eschewing the fanciest public tool if it compromises stability or compliance.
 </li>
 </ul>
 
 
</div>

Senior AI Engineer

Valeo

<div>
 
 
 Mission
 
 
 
 
 <ul>
 <li>
 Utilize AI to improve the efficiency, energy consumption, and overall performance of lighting systems.
 </li>
 <li>
 Leverage synthetic data generated from simulation tools to train and test AI models.
 </li>
 <li>
 Develop AI models that can be easily generalized and parameterized to adapt to different lighting environments and applications.
 </li>
 <li>
 Utilize AI techniques to automate or assist in the annotation of large datasets.
 </li>
 <li>
 Contribute to the development of innovative AI solutions for lighting systems through research, development, and technical publications.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 AI-Driven Lighting Optimization: Employ AI techniques to improve the efficiency, energy consumption, and overall performance of lighting systems. Explore opportunities to enhance lighting control, automation, and user experience.
 </li>
 <li>
 Synthetic Data Utilization: Leverage synthetic data generated from simulation tools to train and test AI models. This will enable more efficient and effective model development, especially in scenarios where real-world data is limited or difficult to obtain.
 </li>
 <li>
 Model Generalization and Parameterization: Develop AI models that can be easily generalized and parameterized to adapt to different lighting environments and applications, and increase the flexibility and scalability of the solutions.
 </li>
 <li>
 Large Dataset Annotation: Utilize AI techniques to automate or assist in the annotation of large datasets. This will streamline the data preparation process and enable more efficient model training.
 </li>
 <li>
 Problem Formulation and Solution Design: Conduct in-depth research to understand and define problems related to lighting systems. Explore and evaluate AI-based algorithms and techniques that can effectively solve these problems. Identify strategies to integrate AI solutions into existing lighting applications.
 </li>
 <li>
 AI Model Development: Create or modify scripts to establish training environments for AI models. Develop new use cases for simulation to enhance model performance. Experiment with different model parameters and environments to optimize training processes. Train and test models to evaluate their accuracy and effectiveness.
 </li>
 <li>
 Data Analysis and Visualization: Analyze datasets to identify potential issues that may impact model accuracy and functionality. Develop insightful data visualizations using dashboards to facilitate data analysis and model evaluation.
 </li>
 <li>
 Documentation and Communication: Document the entire workflow, including research findings, model development processes, and results. Prepare clear and concise presentations to effectively communicate technical concepts and project outcomes.
 </li>
 <li>
 Technical Publications: Contribute to the publication of technical papers or patents when significant milestones are achieved, showcasing your research and development contributions to the field.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or a related field.
 </li>
 <li>
 1+ years of experience in automotive embedded software development
 </li>
 <li>
 Extensive experience in Python programming, including object-oriented programming and proficiency in libraries such as Pandas and NumPy.
 </li>
 <li>
 Solid understanding of machine learning fundamentals, encompassing supervised and unsupervised learning techniques. Experience in data analysis and utilizing tools like scikit-learn.
 </li>
 <li>
 Knowledge of deep learning concepts, including artificial neural networks, recurrent neural networks, and long short-term memory networks. Familiarity with deep learning frameworks like PyTorch and TensorFlow.
 </li>
 <li>
 Basic understanding of reinforcement learning principles and experience with tools like stable-baseline and gym.
 </li>
 <li>
 Knowledge of large language models and generative AI techniques
 </li>
 <li>
 Experience with physics-based simulation platforms such as CARLA, Webots, or SCANeR
 </li>
 <li>
 Strong problem-solving and analytical skills.
 </li>
 <li>
 Ability to work independently and as part of a team.
 </li>
 <li>
 Excellent communication and documentation skills.
 </li>
 <li>
 Passion for AI research and development.
 
 
 </li>
 </ul>
 
 
 Other Specifications
 
 
 
 
 <ul>
 <li>
 Experience in software development for lighting systems in the automotive industry is highly desirable.
 </li>
 <li>
 Proficiency in backend development frameworks such as Flask and React is a plus. Knowledge of other relevant backend technologies is also beneficial.
 </li>
 <li>
 Experience with major cloud platforms like Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure is a plus
 </li>
 <li>
 Solid understanding and experience with C and C++ programming languages is highly desirable.
 </li>
 <li>
 Experience using MATLAB and Simulink for modeling, simulation, and analysis of systems. Familiarity with MATLAB toolboxes relevant to the specific application domain is a plus.
 </li>
 </ul>
</div>

AI Engineer, LIGHT

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 
 
 Mission
 
 
 
 
 <ul>
 <li>
 Utilize AI to improve the efficiency, energy consumption, and overall performance of lighting systems.
 </li>
 <li>
 Leverage synthetic data generated from simulation tools to train and test AI models.
 </li>
 <li>
 Develop AI models that can be easily generalized and parameterized to adapt to different lighting environments and applications.
 </li>
 <li>
 Utilize AI techniques to automate or assist in the annotation of large datasets.
 </li>
 <li>
 Contribute to the development of innovative AI solutions for lighting systems through research, development, and technical publications.
 
 
 </li>
 </ul>
 
 
 Responsibilities
 
 ~
 
 
 
 <ul>
 <li>
 AI-Driven Lighting Optimization~ Employ AI techniques to improve the efficiency, energy consumption, and overall performance of lighting systems. Explore opportunities to enhance lighting control, automation, and user experience.
 </li>
 <li>
 Synthetic Data Utilization~ Leverage synthetic data generated from simulation tools to train and test AI models. This will enable more efficient and effective model development, especially in scenarios where real-world data is limited or difficult to obtain.
 </li>
 <li>
 Model Generalization and Parameterization~ Develop AI models that can be easily generalized and parameterized to adapt to different lighting environments and applications, and increase the flexibility and scalability of the solutions.
 </li>
 <li>
 Large Dataset Annotation~ Utilize AI techniques to automate or assist in the annotation of large datasets. This will streamline the data preparation process and enable more efficient model training.
 </li>
 <li>
 Problem Formulation and Solution Design~ Conduct in-depth research to understand and define problems related to lighting systems. Explore and evaluate AI-based algorithms and techniques that can effectively solve these problems. Identify strategies to integrate AI solutions into existing lighting applications.
 </li>
 <li>
 AI Model Development~ Create or modify scripts to establish training environments for AI models. Develop new use cases for simulation to enhance model performance. Experiment with different model parameters and environments to optimize training processes. Train and test models to evaluate their accuracy and effectiveness.
 </li>
 <li>
 Data Analysis and Visualization~ Analyze datasets to identify potential issues that may impact model accuracy and functionality. Develop insightful data visualizations using dashboards to facilitate data analysis and model evaluation.
 </li>
 <li>
 Documentation and Communication~ Document the entire workflow, including research findings, model development processes, and results. Prepare clear and concise presentations to effectively communicate technical concepts and project outcomes.
 </li>
 <li>
 Technical Publications~ Contribute to the publication of technical papers or patents when significant milestones are achieved, showcasing your research and development contributions to the field.
 
 
 </li>
 </ul>
 
 
 Qualifications
 
 ~
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or a related field.
 </li>
 <li>
 1+ years of experience in automotive embedded software development
 </li>
 <li>
 Extensive experience in Python programming, including object-oriented programming and proficiency in libraries such as Pandas and NumPy.
 </li>
 <li>
 Solid understanding of machine learning fundamentals, encompassing supervised and unsupervised learning techniques. Experience in data analysis and utilizing tools like scikit-learn.
 </li>
 <li>
 Knowledge of deep learning concepts, including artificial neural networks, recurrent neural networks, and long short-term memory networks. Familiarity with deep learning frameworks like PyTorch and TensorFlow.
 </li>
 <li>
 Basic understanding of reinforcement learning principles and experience with tools like stable-baseline and gym.
 </li>
 <li>
 Knowledge of large language models and generative AI techniques
 </li>
 <li>
 Experience with physics-based simulation platforms such as CARLA, Webots, or SCANeR
 </li>
 <li>
 Strong problem-solving and analytical skills.
 </li>
 <li>
 Ability to work independently and as part of a team.
 </li>
 <li>
 Excellent communication and documentation skills.
 </li>
 <li>
 Passion for AI research and development.
 
 
 </li>
 </ul>
 
 
 Other Specifications
 
 
 
 
 <ul>
 <li>
 Experience in software development for lighting systems in the automotive industry is highly desirable.
 </li>
 <li>
 Proficiency in backend development frameworks such as Flask and React is a plus. Knowledge of other relevant backend technologies is also beneficial.
 </li>
 <li>
 Experience with major cloud platforms like Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure is a plus
 </li>
 <li>
 Solid understanding and experience with C and C++ programming languages is highly desirable.
 </li>
 <li>
 Experience using MATLAB and Simulink for modeling, simulation, and analysis of systems. Familiarity with MATLAB toolboxes relevant to the specific application domain is a plus.
 
 
 </li>
 </ul>
 
 Position~
 
 
 
 AI4all, Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 Software Development
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-03-18
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

almentor

<div>
 
 
 About almentor
 
 : almentor is a cutting-edge online video marketplace for e-learning and professional business development throughout the Middle East and Africa. Offering video courses in Arabic and English, we curate top-rated training programs of expert-created content and guided curriculum with interactive delivery.
 
 
 
 
 
 
 Our Mission:
 
 🚀 almentor is on a mission to increase accessibility to affordable quality education for Arabic-speaking communities and a Goal to serve 10 million learners in MENA
 
 
 
 
 
 
 Job Overview:
 
 
 
 Reporting to the Head of Engineering, your role is to design, build, and operate the data and applied AI foundations that power intelligent learning experiences and business workflows. You will ship production- grade pipelines, retrieval/search systems, and LLM-enabled features that are measurable, secure, and reliable.
 
 
 
 
 
 We are committed to building software that is not only functional and reliable, but also beautiful and intuitive. Our engineers and designers work together to create products that are a joy to use, and that solve real-world problems in innovative ways. We believe in the Agile and XP methodologies, and we prioritize collaboration, communication, and continuous improvement in everything we do.
 
 
 
 
 
 We are embarking on an exciting journey of rebuilding our product and engineering organization to drive innovation and growth. Our goal is to create a world-class platform that delivers the best possible learning experiences to our users.
 
 
 Share the journey along with engineers, product managers, and leaders from the most successful organizations in the region.
 
 
 
 
 
 
 As a Senior Data / AI Engineer, your'll spend your time on:
 
 
 <ul>
 <li>
 Blending data engineering, applied AI implementation, and operational ownership.
 </li>
 <li>
 Architect, implement, and maintain pipelines that ingest, transform, and serve data for product features, analytics, and AI workflows.
 </li>
 <li>
 Build indexing and retrieval layers (structured + unstructured) to power search, recommendations, and AI assistants (RAG).
 </li>
 <li>
 Implement LLM-powered features: prompt orchestration, tool/function calling, RAG patterns, structured extraction, summarization.
 </li>
 <li>
 Add guardrails: policy checks, rate limits, cost controls, and safe handling of sensitive data.
 </li>
 <li>
 Create evaluation harnesses and regression tests for retrieval of quality and AI outputs (offline datasets + automated checks).
 </li>
 <li>
 Instrument pipelines/services with logging, tracing, metrics, and data quality monitoring.
 </li>
 <li>
 Partner closely with product managers, designers, and engineers to translate user needs into measurable data/AI capabilities.
 </li>
 <li>
 Participate in sprint planning, refinement, and cross-team alignment to keep execution predictable.
 </li>
 <li>
 Own your pipelines and services in production &mdash; incident response, post-mortems, runbooks, and continuous improvement.
 </li>
 <li>
 Optimize latency, cost, and throughput across data processing, indexing, and AI inference usage.
 </li>
 <li>
 A typical day might look like: checking pipeline freshness and alerts in the morning, tuning chunking/index mappings for a new course search mid-day, pairing with product on evaluation metrics for an AI study
 </li>
 <li>
 Assistant in the afternoon, and ending the day by shipping a monitored RAG endpoint with cost budgets and regression tests.
 </li>
 </ul>
 
 
 Role Objectives
 
 
 <ul>
 <li>
 Design, oversee, build and operate data pipelines and applied AI systems that power our education platform across consumer and business customer segments.
 </li>
 <li>
 Build and scale retrieval and search foundations (hybrid search, metadata filtering, vector retrieval) that enable AI experiences.
 </li>
 <li>
 Deliver production LLM capabilities with measurable quality, cost controls, and safety guardrails.
 </li>
 <li>
 Improve system performance, reliability, observability, and maintainability through proactive monitoring and data quality checks.
 </li>
 <li>
 Collaborate closely with stakeholders (product managers, designers, frontend/mobile engineers) to translate business requirements into technical solutions.
 </li>
 <li>
 Contribute to sprint planning, technical documentation, and cross-team initiatives as a senior engineering voice.
 </li>
 <li>
 Contributing to sprint planning, technical documentation, and cross-team initiatives as a senior voice in the engineering org.
 </li>
 </ul>
 
 
 
 
 
 The ideal candidate will have:
 
 
 <ul>
 <li>
 4+ years of experience in data engineering, backend engineering, or platform engineering, with meaningful production ownership.
 </li>
 <li>
 Strong SQL and data modeling skills; experience designing schemas and data contracts.
 </li>
 <li>
 Experience building and operating pipelines (batch and/or streaming), including backfills and data quality validation.
 </li>
 <li>
 Experience with search/indexing systems and retrieval patterns (e.g., OpenSearch/Elasticsearch, vector DBs, hybrid search).
 </li>
 <li>
 Hands-on experience implementing LLM-powered features (RAG, tool/function calling, prompt/version management) &mdash; no deep ML required.
 </li>
 <li>
 Familiarity with CI/CD, containerization (Docker), and cloud services (ex. AWS, GCP).
 </li>
 <li>
 Strong problem-solving and debugging skills, with a proactive attitude towards owning and improving systems.
 </li>
 <li>
 Strong written and verbal communication skills, with the ability to explain complex ideas clearly to technical and non-technical stakeholders.
 </li>
 <li>
 Bachelor&rsquo;s degree in computer science, Engineering, or a related field is preferred but not required
 </li>
 </ul>
</div>

Senior Data & Applied AI Engineer

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and deploy end-to-end ML/AI solutions. Build and optimize LLM-based systems (Agents, Agentic workflows, RAG pipelines, embeddings, multimodal, etc.).
 </li>
 <li>
 Research, evaluate, and experiment with new AI techniques, models, tools, and frameworks, and assess their feasibility, performance, and business impact.
 </li>
 <li>
 Fine-tune, evaluate, and benchmark systems using quantitative and AI-Based evaluation methods.
 </li>
 <li>
 Stay up to date with advancements in the field. Drive adoption of relevant innovations into production systems.
 </li>
 <li>
 Design AI system architecture with focus on production aspects such as scalability, latency, cost efficiency, and reliability.
 </li>
 <li>
 Collaborate with product, backend, and cloud teams to integrate AI systems.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 4+ years of hands-on experience in AI/ML development.
 </li>
 <li>
 Master&rsquo;s degree (MSc) in AI, Machine Learning, Computer Science, or a related field. (a significant advantage)
 </li>
 <li>
 Solid ML/AI fundamentals.
 </li>
 <li>
 Strong practical experience in AI related developments (Python, frameworks, tools, etc.).
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills.
 </li>
 <li>
 Experience deploying AI solutions to production environments.
 </li>
 <li>
 Experience with cloud AI platforms (e.g., GCP, Vertex AI).
 </li>
 <li>
 Familiarity with MLOps, monitoring, and CI/CD pipelines.
 
 
 </li>
 </ul>
 
 Position~
 
 
 
 R&amp;D Engineer
 
 
 
 D&eacute;partement~
 
 
 
 GTSC Artificial Intelligence
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-01-19
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

Senior AI Engineer, AI4ALL

LeadInTop

<div>
 We are looking for a talented AI Engineer to design, build, and deploy intelligent systems powered by AI technologies. The ideal candidate will work on building AI-driven tools, automations, and applications by integrating AI APIs, and data pipelines.
 
 
 You will be responsible for developing scalable AI solutions that leverage technologies such as LLMs, AI agents, speech recognition, web scraping, and workflow automation.
 
 
 This role requires strong problem-solving skills and the ability to translate business requirements into practical AI systems and automation pipelines.
 
 
 Key Responsibilities
 
 
 Design and build AI-powered applications and tools using modern AI APIs and frameworks.
 
 
 Develop AI agents and automation workflows to streamline business processes.
 
 
 Integrate large language models (LLMs) such as OpenAI and Claude into production systems.
 
 
 Implement web scraping and data extraction pipelines to collect structured data from external sources.
 
 
 Build AI pipelines that process, analyze, and generate insights from large datasets.
 
 
 Develop speech-to-text and audio processing solutions using models like Whisper.
 
 
 Integrate AI services with internal platforms, dashboards, and business tools.
 
 
 Collaborate with product, engineering, and business teams to deliver scalable AI solutions.
 
 
 Continuously research and implement new AI technologies and frameworks.
 
 
 
 
 Requirements
 
 
 Strong experience with Python and JavaScript.
 
 
 Experience working with AI APIs and LLM platforms.
 
 
 Familiarity with AI agent frameworks and prompt engineering.
 
 
 Experience with web scraping tools and data extraction pipelines.
 
 
 Understanding of REST APIs and system integrations.
 
 
 Experience building automation workflows.
 
 
 Ability to design and deploy AI-powered systems in production environments.
 
 
 Tools &amp; Technologies (Preferred)
 
 
 Experience with some of the following tools is a plus:
 
 
 n8n
 
 
 Apify
 
 
 Claude Code
 
 
 Lovable
 
 
 OpenAI Api's
 
 
 Cursor
 
 
 Experience Requirements
 
 
 3+ years experience in software engineering or AI development
 
 
 Hands-on experience building AI-powered applications or automation systems
 
 
 Experience integrating AI models into real-world products
 
 
 What Success Looks Like in This Role
 
 
 Building reliable AI automation pipelines
 
 
 Delivering production-ready AI tools and applications
 
 
 Creating scalable systems that leverage AI to solve real business problems
 
 
 
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