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ai engineer (mid-level/senior)

ai/ml engineer

ml engineer

<div>
 
 Who We Are
 
 
 
 VML, part of WPP, is a leading creative company that combines brand experience, customer experience, and commerce, creating connected brands to drive growth. VML is celebrated for its innovative and human first, award-winning work for blue chip client partners including AstraZeneca, Colgate-Palmolive, Dell, Ford, Microsoft, Nestl&eacute;, The Coca-Cola Company, and Wendy's. The agency is recognized by the Forrester Wave&trade; Reports, as a Leader among Marketing Creative and Content Service Providers, Commerce Services, Global Digital Experience Services, Global Marketing Services and, most recently, Marketing Measurement &amp; Optimization. In addition, VML&rsquo;s specialist health network, VML Health, is one of the world&rsquo;s largest and most awarded health agencies. VML&rsquo;s global network is powered by 26,000 talented people across 55+ markets, with principal offices in Kansas City, New York, Detroit, London, S&atilde;o Paulo, Shanghai, Singapore, and Sydney.
 
 
 
 About WPP
 
 
 
 WPP is the trusted growth partner for the world&rsquo;s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company &ndash; powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. For more information, visit WPP.com.
 
 
 
 Who we&rsquo;re looking for:
 
 We are seeking an experienced AI/ML Engineer with a minimum of 5 years of expertise to join our innovative technology team. In this pivotal role, you will be responsible for designing, training, and optimizing AI models, with a strong focus on Natural Language Processing (NLP) for real-time content summarization, recommendation, and conversational UIs. You will implement cutting-edge techniques like Retrieval-Augmented Generation (RAG) and fine-tune transformer-based models, collaborating closely with backend and data engineering teams to ensure seamless deployment and maintenance of brand tone and content accuracy in all AI outputs.
 
 
 
 What You&rsquo;ll Be Doing
 
 
 
 <ul>
 <li>
 Design, train, and optimize AI models specifically for real-time content summarization and recommendation.
 </li>
 <li>
 Implement advanced Natural Language Processing (NLP) techniques to enhance conversational UI and predictive interactions.
 </li>
 <li>
 Apply Retrieval-Augmented Generation (RAG) for intelligent response generation from dynamic content sources.
 </li>
 <li>
 Fine-tune transformer-based models (e.g., BERT, T5) using domain-specific datasets to achieve optimal performance.
 </li>
 <li>
 Collaborate closely with backend and data engineering teams to streamline model deployment within a production-grade environment.
 </li>
 <li>
 Ensure that brand tone and content accuracy are meticulously maintained throughout all AI-generated outputs.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Need
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
 </li>
 <li>
 5&ndash;7 years of progressive experience in AI/ML engineering, with a strong and proven focus on Natural Language Processing (NLP).
 </li>
 <li>
 Strong practical experience with leading Machine Learning frameworks such as TensorFlow, PyTorch, and Hugging Face.
 </li>
 <li>
 Experience with LangChain and LangGraph.
 </li>
 <li>
 Experience with MLOps pipelines and platforms like AWS SageMaker, Azure AI Search, or similar.
 </li>
 <li>
 Solid understanding of Large Language Models (LLMs), embeddings, and semantic search technologies.
 </li>
 <li>
 Expert proficiency in Python and robust data handling libraries such as Pandas and NumPy.
 </li>
 <li>
 Familiarity with deploying AI models via microservices or APIs.
 </li>
 <li>
 Preferred Qualifications:
 </li>
 <li>
 Understanding of branding, tone, and the user experience (UX) implications in AI-generated content.
 </li>
 <li>
 Experience working with headless CMS (Content Management Systems) and structured content datasets.
 </li>
 <li>
 Knowledge of ethical AI principles and prompt engineering best practices.
 
 
 </li>
 </ul>
 
 Additional Competencies
 
 
 
 <ul>
 <li>
 AI/ML Engineering
 </li>
 <li>
 Natural Language Processing (NLP)
 </li>
 <li>
 Large Language Models (LLMs)
 </li>
 <li>
 MLOps &amp; Deployment
 </li>
 <li>
 Python &amp; Data Science
 </li>
 <li>
 Transformer Models
 </li>
 <li>
 Content Summarization &amp; Recommendation
 </li>
 <li>
 Brand &amp; Content Integrity
 
 
 </li>
 </ul>
 We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we&rsquo;ve adopted a hybrid approach, with teams in the office an average of four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.
 
 
 WPP (VML) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.
 
 
 VML is a WPP agency (NYSE: WPP). For more information, please visit  www.vml.com, and follow along on Instagram, LinkedIn, and X.
 
 
 When you click "Submit Application", this will send any information you add below to VML. Before you do this, we think it's a good idea to read through our Recruitment Privacy Policy. California residents should read our California Recruitment Privacy Notice. This explains what we do with your personal data when you apply for a role with us, and, how you can update the information you have provided us with or how to remove it.
</div>

AI/ML Engineer

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Senior Machine Learning Engineer

<div>
 Siemens Digital Industries (DI) is a global leader in automation and digitalization. In close collaboration with partners and customers, we drive digital transformation across process and discrete industries. Our Digital Enterprise portfolio delivers an end-to-end ecosystem of products, solutions, and services that help organizations of all sizes integrate and digitalize their entire value chain.
 
 
 Our industry-focused portfolio enables customers to achieve greater efficiency, flexibility, and innovation. We continuously evolve our technology stack by integrating groundbreaking future technologies. Siemens Digital Industries Software is headquartered in Nuremberg, Germany, and employs approximately 75,000 people worldwide.
 
 
 We offer a role that combines responsibility, autonomy, and the opportunity to contribute proactively. Our culture promotes teamwork, ownership, and continuous individual development.
 
 
 Learn more: https://siemensneo.com/disw/
 
 
 We're looking for a
 
 Principal Machine Learning Engineer
 
 to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and deliver RAG pipelines, prompt workflows, agent tools, safety guardrails, and evaluation frameworks &mdash; optimizing for performance, cost, and quality.
 </li>
 <li>
 Own the ML lifecycle end-to-end: From data prep and feature engineering to fine-tuning (LoRA/QLoRA), testing, deployment, monitoring, and continuous improvement.
 </li>
 <li>
 Productionize on AWS: Launch scalable ML services using AWS infrastructure and ML tooling, with strong observability and cost efficiency.
 </li>
 <li>
 Scale training &amp; inference: Apply distributed training, quantization, caching, and vector databases to improve performance and efficiency.
 </li>
 <li>
 Drive MLOps &amp; governance: Build CI/CD pipelines for ML, manage model/version registries, track experiments, and enforce responsible AI practices.
 </li>
 <li>
 Partner cross-functionally: Work with product and engineering teams to turn real asset-management problems into customer-facing ML solutions.
 </li>
 <li>
 Mentor &amp; lead: Provide technical guidance, review designs, and elevate ML engineering standards across the team.
 </li>
 <li>
 Analyze data deeply: Perform EDA on structured and unstructured data to uncover insights, patterns, and quality issues.
 </li>
 <li>
 Research domain signals: Investigate operational and asset datasets to identify trends, root causes, and predictive opportunities.
 
 
 </li>
 </ul>
 Qualifications:
 
 
 <ul>
 <li>
 B.Sc. in Computer Engineering or Electronics Engineering.
 </li>
 <li>
 10+ years in software/ML engineering, including 3+ years running production ML systems end-to-end.
 </li>
 <li>
 Hands-on experience building LLM applications (RAG, fine-tuning, prompt engineering, evaluators/guardrails, agent workflows) using tools like LangChain/LangGraph.
 </li>
 <li>
 Strong AWS background (3+ years), including core infrastructure and ML services such as SageMaker and Bedrock.
 </li>
 <li>
 Solid modeling stack: Python, PyTorch, Hugging Face, embeddings/vector databases, and LLM evaluation techniques.
 </li>
 <li>
 Proven MLOps experience: CI/CD for ML, experiment tracking, model registries, monitoring, and automated retraining pipelines.
 </li>
 <li>
 Good data engineering foundations: ETL/ELT pipelines, streaming/batch processing (Spark/Flink), and data governance practices.
 </li>
 <li>
 Experience with distributed training, RLHF, or optimization on specialized AI hardware is a plus!
 </li>
 <li>
 Preferrably has background in asset, sustainability, or intelligent operations domains.
 </li>
 <li>
 Familiarity with enterprise ML security and compliance practices is nice to have.
 
 
 </li>
 </ul>
 We&rsquo;re Siemens. A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit and business need. Bring your curiosity and creativity and help us shape tomorrow!
 
 
 Siemens is an equal opportunities employer and do not discriminate unlawfully on any grounds. We are committed to providing access and equal opportunity.
</div>

Principal Machine Learning Engineer

700apps

<div>
 We are looking for a highly skilled
 
 Senior AI Engineer / AI Architect
 
 to lead the design, development, and deployment of scalable AI solutions.
 
 
 In this role, you will combine hands-on model development with high-level system architecture to help shape our AI strategy and deliver production-ready intelligent systems.
 
 
 You will work closely with engineering, product, and leadership teams to transform business needs into powerful AI-driven solutions.
 
 
 
 Key Responsibilities
 
 
 
 AI Architecture &amp; System Design
 
 
 <ul>
 <li>
 Design end-to-end AI/ML system architecture from data ingestion to deployment and monitoring.
 </li>
 <li>
 Define scalable and reliable ML pipelines.
 </li>
 <li>
 Select the appropriate tools, frameworks, and infrastructure.
 </li>
 <li>
 Ensure performance, security, scalability, and maintainability of AI systems.
 </li>
 <li>
 Design APIs and AI services for integration with products and platforms.
 
 
 </li>
 </ul>
 Model Development
 
 
 <ul>
 <li>
 Develop, train, and fine-tune machine learning and deep learning models.
 </li>
 <li>
 Work on advanced AI solutions such as LLMs, NLP systems, or computer vision models.
 </li>
 <li>
 Optimize models for accuracy, speed, and cost efficiency.
 </li>
 <li>
 Conduct experiments and evaluate model performance using best practices.
 
 
 </li>
 </ul>
 MLOps &amp; Deployment
 
 
 <ul>
 <li>
 Build and maintain CI/CD pipelines for machine learning workflows.
 </li>
 <li>
 Deploy models to production using containers and cloud services.
 </li>
 <li>
 Implement monitoring, logging, and automated retraining processes.
 </li>
 <li>
 Manage model lifecycle, versioning, and performance tracking.
 
 
 </li>
 </ul>
 Technical Leadership
 
 
 <ul>
 <li>
 Provide technical leadership to AI engineers and data scientists.
 </li>
 <li>
 Review code and guide best practices in AI development.
 </li>
 <li>
 Collaborate with cross-functional teams to align AI solutions with business goals.
 </li>
 <li>
 Contribute to technical strategy and AI roadmap planning.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 7+ years of experience in AI / Machine Learning engineering.
 </li>
 <li>
 Strong programming skills in Python.
 </li>
 <li>
 Hands-on experience with PyTorch or TensorFlow.
 </li>
 <li>
 Experience working with LLMs and modern AI frameworks.
 </li>
 <li>
 Strong understanding of system design and scalable architectures.
 </li>
 <li>
 Experience with cloud platforms such as AWS, GCP, or Azure.
 </li>
 <li>
 Experience with Docker and Kubernetes.
 </li>
 <li>
 Familiarity with MLOps tools such as MLflow, Airflow, or similar.
 </li>
 <li>
 Solid understanding of data pipelines and data engineering concepts.
 </li>
 </ul>
</div>

AI Architect

InVitro Capital

<div>
 
 
 About InVitro Capital:
 
 
 
 
 
 
 InVitro Capital is a U.S.-based venture studio and fund. We build and fund companies from idea to exit, focusing on technology-driven businesses that solve real-world problems. Our portfolio spans healthcare, home services, and sales technology.
 
 
 Our engineering philosophy is simple: small senior teams, extreme ownership, hands-on builders, and AI-native products. We do not bolt AI onto products &mdash; we design AI-native systems from day one.
 
 
 We operate with a builder culture where engineers have end-to-end responsibility for launching and scaling AI-powered products across the studio.
 
 
 
 
 
 
 Role Overview:
 
 
 
 
 
 
 We are looking for an exceptionally strong Tech Lead (AI + Full Stack) who codes every day and leads through architecture, execution, and example. This role is designed for elite senior builders who thrive in zero-to-one environments, enjoy solving complex problems, and can ship production-grade systems quickly.
 
 
 This is a full-stack tech lead role first: you will architect and ship end-to-end product systems (backend + frontend collaboration), and you must also be strong enough in AI/ML to build and productionize AI capabilities inside those systems.
 
 
 
 
 
 You will:
 
 <ul>
 <li>
 Architect core systems
 </li>
 <li>
 Build them with your own hands
 </li>
 <li>
 Integrate AI tooling &amp; agents
 </li>
 <li>
 Mentor engineers through technical leadership
 </li>
 <li>
 Drive engineering excellence across multiple ventures
 </li>
 </ul>
 
 This is not a people-management role &mdash; it is a high-impact IC leadership role.
 
 
 
 
 
 
 What You'll Do:
 
 
 
 
 
 
 
 Build &amp; Lead With Technical Depth (70-90% hands-on)
 
 
 <ul>
 <li>
 Architect, build, and ship backend and full-stack systems end to end.
 </li>
 <li>
 Lead engineers through code reviews, architecture reviews, and solid technical decision-making.
 </li>
 <li>
 Own engineering execution across multiple ventures.
 </li>
 </ul>
 
 
 
 
 
 Design Scalable, AI-Native Architectures
 
 
 <ul>
 <li>
 Build modular APIs, distributed systems.
 </li>
 <li>
 Embed AI capabilities into product systems (LLMs and/or domain AI like NLP/CV) in a way that is secure, observable, reliable, and scalable.
 </li>
 <li>
 Design and implement retrieval workflows (RAG), evaluation/guardrails, and agent/tool orchestration where they add real product value.
 </li>
 <li>
 Work with Python, OpenAI, Anthropic, LangGraph, LangChain, LlamaIndex, vector databases, and agent toolchains.
 </li>
 </ul>
 
 
 
 
 
 Engineer With Excellence
 
 
 <ul>
 <li>
 Write high-performance, production-grade code in Python (primary) for backend services and AI/ML systems.
 </li>
 <li>
 Build and productionize ML/AI components (training/inference pipelines, model serving, and integrations) with strong engineering discipline.
 </li>
 <li>
 Build systems optimized for reliability, performance, and observability.
 </li>
 </ul>
 
 
 
 
 
 Full-Stack Ownership
 
 
 <ul>
 <li>
 Collaborate with frontend engineers to deliver seamless end-to-end experiences.
 </li>
 <li>
 Design clean APIs, interfaces, and developer workflows.
 </li>
 </ul>
 
 
 
 
 
 DevOps + Cloud Execution
 
 
 <ul>
 <li>
 Manage CI/CD pipelines and cloud deployments on AWS.
 </li>
 <li>
 Kubernetes is a strong plus; AWS + Docker + CI/CD and production deployment ownership are required.
 </li>
 <li>
 Ensure systems are scalable, fault-tolerant, secure, and well-instrumented.
 </li>
 <li>
 Own production deployments of AI/ML components (model serving, monitoring, and lifecycle workflows) alongside the core application stack.
 </li>
 </ul>
 
 
 
 
 
 Technical Leadership &amp; Mentorship
 
 
 <ul>
 <li>
 Mentor engineers and uplift technical standards across the stack.
 </li>
 <li>
 Provide architectural direction and guide complex technical initiatives.
 </li>
 <li>
 Contribute to hiring and shaping engineering culture.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 
 
 
 Required:
 
 
 <ul>
 <li>
 Professional Engineering Experience &mdash; 12+ years building and shipping production-grade systems.
 </li>
 <li>
 Python Expertise (FastAPI or similar, production) &mdash; async services, Pydantic models, you write Python daily.
 </li>
 <li>
 Backend/System Architecture Ownership &mdash; you've owned system design decisions, led code reviews, mentored engineers, and shipped end-to-end systems as a senior IC or tech lead.
 </li>
 <li>
 Core ML / Deep Learning (hands-on) &mdash; built ML/DL systems using PyTorch or TensorFlow; understand training, evaluation, optimization.
 </li>
 <li>
 Production ML Deployment / MLOps &mdash; deployed ML systems to production; owned monitoring, versioning, rollback strategies, lifecycle management.
 </li>
 <li>
 Applied AI Systems Experience &mdash; shipped AI-powered features using LLMs and/or applied NLP/CV in real products (not experimentation only).
 </li>
 <li>
 PostgreSQL &mdash; schema design, query optimization, migrations.
 </li>
 <li>
 Cloud + Delivery &mdash; AWS + Docker + CI/CD; production deployments and operational ownership.
 </li>
 <li>
 REST API Design &mdash; clean interfaces serving multiple clients (web, mobile, service-to-service).
 </li>
 <li>
 Startup Execution &mdash; experience in fast-paced, high-ownership environments.
 </li>
 </ul>
 
 
 
 
 
 Strong Plus:
 
 
 <ul>
 <li>
 Ruby on Rails (production) &mdash; built and maintained real Rails APIs with background jobs (e.g., Sidekiq), webhooks, and complex domain logic.
 </li>
 <li>
 Kubernetes (production) &mdash; EKS (or equivalent), Kubernetes-based deployments, operational ownership.
 </li>
 <li>
 GenAI Depth &mdash; experience designing RAG systems, prompt strategies, fine-tuning workflows, and evaluation/guardrails.
 </li>
 <li>
 Retrieval &amp; Vector Systems &mdash; vector databases (Pinecone, Weaviate, or similar), embedding strategies, namespace/tenancy design, reranking.
 </li>
 <li>
 Agent Orchestration &mdash; multi-agent patterns, tool use, chain composition (CrewAI, LangGraph, or similar).
 </li>
 <li>
 AI Tooling Ecosystem &mdash; LangChain, LlamaIndex, Hugging Face, or similar; LLM observability/tracing (LangSmith or equivalent).
 </li>
 <li>
 Full-Stack Fluency &mdash; strong collaboration with frontend teams to ship end-to-end product experiences; clean API contracts.
 </li>
 <li>
 React 19 (JavaScript) &mdash; Redux Toolkit, RTK Query, Vite, shadcn/ui.
 </li>
 <li>
 Flutter/Dart &mdash; mobile app development, BLoC pattern, Clean Architecture.
 </li>
 <li>
 Firebase/Firestore &mdash; real-time sync, Cloud Functions.
 </li>
 <li>
 Stripe &mdash; payment processing, webhook-driven architecture, Connect.
 </li>
 <li>
 MongoDB &mdash; document modeling; async drivers (Motor) is a plus.
 </li>
 <li>
 Multimodal AI &mdash; vision models; real-time audio/video AI (LiveKit, OpenAI Realtime API).
 </li>
 <li>
 Redis + Sidekiq &mdash; background job processing, caching.
 </li>
 <li>
 0&rarr;1 / Venture Studio Experience &mdash; building products from scratch in multi-product, high-velocity environments.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 Compensation: $4,000-$5,000 USD/month base + bonus
 </li>
 <li>
 Health insurance
 </li>
 <li>
 Social insurance
 </li>
 <li>
 Paid Time Off (PTO)
 </li>
 <li>
 High ownership and autonomy
 </li>
 <li>
 Opportunity to build multiple AI-powered products from scratch
 </li>
 <li>
 A culture optimized for speed, impact, and technical excellence
 </li>
 </ul>
 
 
 
 
 
 Schedule &amp; Work Setup
 
 
 <ul>
 <li>
 Cairo-based candidates preferred
 </li>
 <li>
 Hybrid: expected at the Cairo office at least once per week
 </li>
 <li>
 Monday-Friday, aligned with U.S. Pacific Time
 </li>
 <li>
 High-autonomy, high-velocity engineering environment
 </li>
 </ul>
</div>

Tech Lead (AI + Full Stack/ Python) - Hands-On Builder

Orange Business

<div>
 
 About Us
 
 
 
 Join us at Orange Business!
 
 
 We are a network and digital integrator that understands the entire value chain of the digital world, freeing our customers to focus on the strategic initiatives that shape their business.
 
 
 Every day, you will collaborate with a team dedicated to providing consistent, sustainable global solutions, no matter where our customers operate. With over 30,000 employees across Asia, the Americas, Africa, and Europe, we offer a dynamic environment to develop and perfect your skills in a field filled with exciting challenges and opportunities.
 
 
 
 About The Role
 
 
 
 
 
 About the AI Factory Team
 
 
 
 
 The
 
 AI Factory
 
 team builds intelligent software tools and platforms that empower our business teams including Marketing, Operations, and Sales to leverage AI for productivity, automation, and data-driven decision-making.
 
 
 
 
 Role Overview
 
 
 
 
 We&rsquo;re looking for a
 
 Full Stack AI Software Engineer
 
 with strong AI/ML experience to join our AI Factory team.
 
 
 You&rsquo;ll work on designing, developing, and deploying scalable, production-grade applications that integrate Large Language Models, Generative AI, and data pipelines.
 
 
 You will collaborate closely with data scientists, AI researchers, and business stakeholders to turn ideas into impactful AI-powered software products.
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 Design and develop end-to-end AI-powered applications and internal tools for business teams.
 </li>
 <li>
 Build and maintain full-stack applications using React (frontend) and Python/FastAPI (backend).
 </li>
 <li>
 Implement and optimize LLM-based systems, including RAG pipelines, prompt engineering, and model integration.
 </li>
 <li>
 Collaborate with AI/ML engineers to productionize models and integrate them into user-facing products.
 </li>
 <li>
 Deploy, monitor, and maintain applications using Docker and Kubernetes.
 </li>
 <li>
 Contribute to the AI Factory platform by developing reusable components, APIs, and SDKs.
 </li>
 <li>
 Ensure software quality through testing, CI/CD pipelines, and DevOps best practices.
 </li>
 <li>
 Stay updated on the latest trends in AI/ML, Generative AI, and LLM frameworks (LangChain, LlamaIndex, etc.).
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 
 About you
 
 
 
 <ul>
 <li>
 3+ years of professional experience as a Software Engineer.
 </li>
 <li>
 Strong full-stack development skills
 </li>
 <li>
 Proven experience building AI-driven applications, especially with LLMs, Generative AI, or RAG systems.
 </li>
 <li>
 Hands-on experience with containerization and orchestration tools (Docker, Kubernetes).
 </li>
 <li>
 Familiarity with cloud platforms (AWS, Azure, or GCP) and CI/CD pipelines.
 </li>
 <li>
 Solid understanding of RESTful APIs, microservices, and system design.
 </li>
 <li>
 Strong problem-solving skills, with a collaborative and pragmatic mindset.
 
 
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 
 
 <ul>
 <li>
 Experience with LangChain, LlamaIndex, or similar LLM frameworks.
 </li>
 <li>
 Knowledge of vector databases (e.g., PostgreSql, Pinecone, Weaviate, FAISS).
 </li>
 <li>
 Exposure to MLOps and AI model lifecycle management.
 </li>
 <li>
 Familiarity with prompt engineering and AI agent frameworks.
 </li>
 <li>
 Experience building internal tools or platforms for cross-functional teams.
 
 
 </li>
 </ul>
 You bring passion, energy, taste for exploration and adaptability. You seek the opportunity to expand your knowledge and develop new skills.
 
 
 
 What We Offer
 
 
 
 <ul>
 <li>
 Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
 </li>
 <li>
 Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
 </li>
 <li>
 Professional Development: training programs and upskilling/re-skilling opportunities.
 </li>
 <li>
 Career Growth: Internal growth and mobility opportunities within Orange.
 </li>
 <li>
 Caring and Daring Culture: Health and well-being programs and benefits, diversity &amp; inclusion initiatives, CSR and employee connect events.
 </li>
 <li>
 Reward Programs: Employee Referral Program, Change Maker Awards.
 
 
 </li>
 </ul>
 
 Only Your Skills Matter
 
 
 
 Regardless of your age, gender identity, race, ethnic origin, religion/belief, sexual orientation, marital status, neuroatypia, disability, veteran status or appearance, we encourage diversity within our teams because it is a strength for the collective and a vector of innovation. Orange Group is a disabled-friendly company and equal opportunity employer: don't hesitate to tell us about your specific needs.
</div>

Full Stack AI Software Engineer

HireOn

<div>
 
 Lead Data Scientist &ndash; GenAI (Generative AI)
 
 
 
 Experience: 10+ Years
 
 
 Location: Cairo, Egypt (onsite;
 
 in-office job
 
 )
 
 
 Employment Type: Full-Time
 
 
 
 About The Role
 
 
 
 Our client, a global AWS Consulting Partner with distributed teams across the US, Canada, UAE and Asian region, is hiring
 
 high-caliber Lead Generative AI Engineers.
 
 
 
 This role is ideal for someone who has
 
 10+ years
 
 of software engineering and AI/ML experience and is now focused on
 
 tool-using LLMs, LangChain, AutoGPT, or similar frameworks
 
 .
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Lead the design and architecture of AI-powered enterprise solutions.
 </li>
 <li>
 Drive technical decisions across infrastructure, databases, APIs, microservices, and AI components.
 </li>
 <li>
 Deploy LLMs and GenAI applications in production environments.
 </li>
 <li>
 Provide guidance on prompt engineering, Chain-of-Thought, and advanced AI/ML techniques.
 </li>
 <li>
 Integrate AI/ML models with enterprise systems for high performance and scalability.
 </li>
 <li>
 Mentor and manage technical teams, ensuring knowledge transfer and best practices.
 </li>
 <li>
 Lead AI/ML projects from conceptualization to delivery, including cloud and hybrid deployments.
 </li>
 <li>
 Lead multi-agent systems, and RAG workflow implementations.
 
 
 </li>
 </ul>
 
 Technical Requirements
 
 
 
 <ul>
 <li>
 GenAI Expertise: Hands-on experience with LLM fine-tuning and production deployment.
 </li>
 <li>
 AI/ML &amp; Enterprise Architecture: Experience in Python, TensorFlow, PyTorch, full-stack development, Kubernetes, SQL/NoSQL databases, APIs, and microservices.
 
 
 </li>
 </ul>
 Skills: langchain,autogpt,prompt engineering,ai application development,openai,llama2,vector databases,llm frameworks,gemini,embedding models,agentic ai,generative ai,semantic kernel,rag,crewai,agents
</div>

Lead Data Scientist - AI/ML (Generative AI)

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