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Finaira

<div>
 
 The Senior AI Engineer is a senior individual contributor with deep expertise in a specific domain of AI/ML, responsible for tackling the most complex technical challenges, driving architectural decisions for critical AI components, and setting technical standards. This role requires a blend of advanced research understanding and robust engineering skills to bring cutting-edge AI innovations into production.
 
 
 
 
 
 The difference you will make:
 
 <ul>
 <li>
 Act as a subject matter expert in one or more specialized AI/ML domains (e.g., Generative AI, Explainable AI, Large Language Models, Reinforcement Learning, Real-time Anomaly Detection).
 </li>
 <li>
 Lead the design and implementation of highly scalable, fault-tolerant, and high-performance AI systems and infrastructure.
 </li>
 <li>
 Evaluate and integrate new AI/ML research, algorithms, and technologies into product development.
 </li>
 <li>
 Drive continuous improvement in MLOps, model monitoring, and model governance frameworks.
 </li>
 <li>
 Provide expert technical guidance and mentorship to other AI Engineer 1s and Associates. &bull; Conduct complex performance tuning, optimization, and debugging of AI/ML models and pipelines.
 </li>
 <li>
 Participate in strategic planning for AI initiatives, identifying opportunities for technological advancement.
 </li>
 <li>
 Influence technical direction and architecture discussions within the AI/ML team and across engineering.
 </li>
 <li>
 Lead code reviews for critical components, ensuring architectural integrity, performance, and maintainability.
 </li>
 </ul>
 
 
 
 
 What you will bring to the role:
 
 
 
 Education:
 
 Bachelor&rsquo;s degree or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.
 
 
 
 
 
 
 Experience:
 
 
 <ul>
 <li>
 5+ years of progressive experience in AI/ML engineering, with a proven track record of designing and deploying complex AI systems into production. Demonstrated deep expertise in a specific AI sub-field.
 </li>
 </ul>
 
 
 Technical Skills:
 
 
 <ul>
 <li>
 Expert-level proficiency in Python and advanced ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
 </li>
 <li>
 Extensive experience with cloud-native AI/ML services and distributed computing frameworks (e.g., Spark, Ray).
 </li>
 <li>
 Deep understanding and hands-on experience with MLOps best practices, including CI/CD, model serving, and monitoring in production environments.
 </li>
 <li>
 Strong architectural design skills for complex data pipelines and scalable AI inference systems.
 </li>
 <li>
 Proficiency in system design, distributed systems, and performance optimization. o Ability to critically evaluate and apply academic research to real-world problems.
 </li>
 </ul>
 
 
 Soft Skills:
 
 
 <ul>
 <li>
 Strong ownership and accountability for assigned work.
 </li>
 <li>
 Clear and professional verbal and written communication.
 </li>
 <li>
 Effective time management and task prioritization.
 </li>
 <li>
 Analytical thinking and problem-solving skills.
 </li>
 <li>
 Ability to work independently, collaborate effectively and mentor junior team members.
 </li>
 <li>
 Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
 </li>
 <li>
 Adaptability and learning agility in a fast-paced environment.
 </li>
 <li>
 Strong attention to detail and a commitment to quality.
 </li>
 <li>
 Receptiveness to feedback and continuous improvement mindset
 </li>
 </ul>
 
 
 
</div>

Senior AI Engineer

<div>
 The Senior AI Engineer is a senior individual contributor with deep expertise in a specific domain of AI/ML, responsible for tackling the most complex technical challenges, driving architectural decisions for critical AI components, and setting technical standards. This role requires a blend of advanced research understanding and robust engineering skills to bring cutting-edge AI innovations into production.
 
 
 
 The difference you will make
 
 
 
 <ul>
 <li>
 Act as a subject matter expert in one or more specialized AI/ML domains (e.g., Generative AI, Explainable AI, Large Language Models, Reinforcement Learning, Real-time Anomaly Detection).
 </li>
 <li>
 Lead the design and implementation of highly scalable, fault-tolerant, and high-performance AI systems and infrastructure.
 </li>
 <li>
 Evaluate and integrate new AI/ML research, algorithms, and technologies into product development.
 </li>
 <li>
 Drive continuous improvement in MLOps, model monitoring, and model governance frameworks.
 </li>
 <li>
 Provide expert technical guidance and mentorship to other AI Engineer 1s and Associates.
 </li>
 <li>
 Conduct complex performance tuning, optimization, and debugging of AI/ML models and pipelines.
 </li>
 <li>
 Participate in strategic planning for AI initiatives, identifying opportunities for technological advancement.
 </li>
 <li>
 Influence technical direction and architecture discussions within the AI/ML team and across engineering.
 </li>
 <li>
 Lead code reviews for critical components, ensuring architectural integrity, performance, and maintainability
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 Education:
 
 
 Bachelor's degree or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.
 
 
 Experience:
 
 
 <ul>
 <li>
 5+ years of progressive experience in AI/ML engineering, with a proven track record of designing and deploying complex AI systems into production.
 </li>
 <li>
 Demonstrated deep expertise in a specific AI sub-field
 
 
 </li>
 </ul>
 Technical Skills:
 
 
 <ul>
 <li>
 Expert-level proficiency in Python and advanced ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
 </li>
 <li>
 Extensive experience with cloud-native AI/ML services and distributed computing frameworks (e.g., Spark, Ray).
 </li>
 <li>
 Deep understanding and hands-on experience with MLOps best practices, including CI/CD, model serving, and monitoring in production environments.
 </li>
 <li>
 Strong architectural design skills for complex data pipelines and scalable AI inference systems.
 </li>
 <li>
 Proficiency in system design, distributed systems, and performance optimization.
 </li>
 <li>
 Ability to critically evaluate and apply academic research to real-world problems
 
 
 </li>
 </ul>
 Soft Skills:
 
 
 <ul>
 <li>
 Strong ownership and accountability for assigned work.
 </li>
 <li>
 Clear and professional verbal and written communication.
 </li>
 <li>
 Effective time management and task prioritization. o Analytical thinking and problem-solving skills.
 </li>
 <li>
 Ability to work independently, collaborate effectively and mentor junior team members.
 </li>
 <li>
 Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
 </li>
 <li>
 Adaptability and learning agility in a fast-paced environment.
 </li>
 <li>
 Strong attention to detail and a commitment to quality.
 </li>
 <li>
 Receptiveness to feedback and continuous improvement mindset
 </li>
 </ul>
</div>

Valeo

<div>
 
 You will be joining the
 
 AI4ALL
 
 initiative within our Group IS Application Center (GISACC). This agile team is dedicated to revolutionizing our products and internal tools by harnessing the power of cutting-edge
 
 Generative AI
 
 . We aim to build scalable, serverless, and intelligent applications that seamlessly integrate into Valeo&rsquo;s workflow.
 
 
 
 
 
 Mission
 
 
 
 
 
 As a
 
 Senior AI Data Engineer
 
 , you will bridge the gap between raw enterprise data and our Generative AI ecosystem. You will architect the "nervous system" of our AI models, ensuring our LLMs have access to high-quality, real-time, and contextually relevant data to power the next generation of Valeo&rsquo;s Software Defined Vehicle (SDV) tools and internal processes.
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 Advanced RAG Architecture: Design and implement end-to-end pipelines for Retrieval-Augmented Generation (RAG), including advanced retrieval techniques, Graph RAG, Agentic RAG, and multimodal RAG.
 </li>
 <li>
 Vector Database Management: Architect and optimize vector stores (e.g., Qdrant, Pinecone) to handle high-dimensional embeddings and ensure low-latency similarity searches.
 </li>
 <li>
 Data Connectivity: Design, develop, and maintain secure data connectors to pull information from various external tools, SaaS platforms, and internal databases.
 </li>
 <li>
 Data Pre-processing for Gen-AI: Develop cleaning and normalization workflows specifically for unstructured data (PDFs, HTML, Markdown) to ensure optimal LLM performance.
 </li>
 <li>
 Orchestration: Use tools like LangChain, LlamaIndex, or Haystack to orchestrate complex data flows between storage, embedding models, and LLM endpoints.
 </li>
 <li>
 Monitoring &amp; Evaluation: Implement "RAG-as-a-service" monitoring to track retrieval quality (faithfulness, relevancy) and data drift in production.
 
 
 </li>
 </ul>
 
 
 Candidate Profile
 
 
 
 
 <ul>
 <li>
 Education: B.Sc. or M.Sc. in Computer Science, Data Engineering, or a related field.
 </li>
 <li>
 Experience: 5+ years in Data Engineering with a recent focus on AI/ML pipelines.
 </li>
 <li>
 Technical Skills:
 </li>
 <ul>
 <li>
 Languages: Expert proficiency in Python and SQL; knowledge of Java or Go is a plus.
 </li>
 <li>
 Data Tools: Experience with Spark, Kafka, Airflow/Prefect, and dbt.
 </li>
 <li>
 AI Frameworks: Hands-on experience with LangChain, LlamaIndex, OpenAI API, Hugging Face, MCP, A2A, and ADK.
 </li>
 <li>
 Vector DBs: Proficiency with Qdrant, Pinecone, Chroma, Weaviate, or pgvector.
 </li>
 <li>
 Cloud/DevOps: Knowledge of GCP/AWS, Docker, and Kubernetes.
 </li>
 </ul>
 <li>
 Preferred: Deep understanding of embedding models, chunking strategies, and unstructured data extraction tools (e.g., Unstructured.io, PyMuPDF).
 </li>
 </ul>
</div>

Senior AI Data Engineer, AI4ALL

Deloitte

<div>
 
 Deloitte Innovation Hub | AI &amp; Data | Senior AI / ML Engineer, Cairo, Egypt
 
 
 
 
 Connect to your career at Deloitte
 
 
 
 Deloitte, established globally in 1845, is the world&rsquo;s largest and leading professional services firm, providing Audit &amp; Assurance, Tax &amp; Legal and Consulting and related services to public and private clients spanning multiple industries. Present in more than 150 countries, Deloitte is distinct in its ability to help clients solve their most complex problems, from strategy to implementation.
 
 
 Deloitte innovation hub (DIH) is a strategic initiative established by Deloitte North &amp; South Europe (NSE) to support our ambition to become the leading business transformation partner of choice for our clients and to expand and scale our delivery footprint across EMEA. With access to a scaled, diverse, highly skilled, motivated, and engaged workforce, DIH is delivering complex technical solutions for clients&rsquo; most complex business problems, across portfolios that include &lsquo;Strategy &amp; Transactions&rsquo;, &lsquo;Customer&rsquo;, &lsquo;Engineering, AI &amp; Data, &lsquo;Enterprise, Technology &amp; Performance&rsquo; and &lsquo;Cyber&rsquo;. DIH is aiming to become the destination for top talents in Egypt for a long, exciting career.
 
 
 We invest in outstanding people of diverse talents and backgrounds and empower them to achieve more than they could elsewhere. Our work combines advice with action and integrity. We believe that when our clients and society are stronger, so are we. Our organization has grown in scale and diversity, providing services across the region, with our shared culture remaining the same. We aim to help clients realize their ambitions, make a positive difference in society, and maximize the success of our people. This drive fuels the commitment and humanity that run deep through our every action.
 
 
 
 Connect to your opportunity.
 
 
 
 We are seeking committed new talent to join our AI &amp; Data team. Our goal is to work together with our clients to drive innovation and insight from their data, using cutting edge Data Science and Machine Learning techniques alongside Digital Transformation.
 
 
 As a Senior AI/ML Engineer in our team, you will:
 
 
 <ul>
 <li>
 Apply data science and machine learning techniques creatively to solve complex problems.
 </li>
 <li>
 Research and develop innovative solutions.
 </li>
 <li>
 Stay abreast in new machine learning techniques and data technologies.
 </li>
 <li>
 Participate in all phases of the data science lifecycle from PoC to fully tested productionized solutions.
 </li>
 <li>
 Prepare technical documentation.
 </li>
 <li>
 Ensure high-quality delivery of key parts of our engagements working with our senior data scientists.
 </li>
 <li>
 Suggest practical solutions to clients and work to implement these solutions as a part of larger project teams.
 </li>
 <li>
 Assist in the crafting of responses to client proposal requests and in pitching data science projects to client.
 
 
 </li>
 </ul>
 
 Client Engagement
 
 
 
 Your Tasks would include
 
 :
 
 
 
 <ul>
 <li>
 Engage with clients to understand their pain points and requirements.
 </li>
 <li>
 Communicate solutions/propositions effectively back to client/team.
 
 
 </li>
 </ul>
 
 Data Analysis And Pre-processing
 
 
 
 <ul>
 <li>
 Collect and clean large datasets for machine learning projects.
 </li>
 <li>
 Explore data to identify patterns, anomalies, and potential insights.
 </li>
 <li>
 Pre-process data, including feature engineering and normalization.
 
 
 </li>
 </ul>
 
 Algorithm Development
 
 
 
 <ul>
 <li>
 Design, develop, and implement machine learning algorithms.
 </li>
 <li>
 Experiment with various machine learning models and techniques.
 </li>
 <li>
 Optimize algorithms for accuracy, efficiency, and scalability.
 
 
 </li>
 </ul>
 
 Model Training And Evaluation
 
 
 
 <ul>
 <li>
 Train machine learning models using collected data.
 </li>
 <li>
 Perform testing to validate models.
 </li>
 <li>
 Evaluate model performance using appropriate metrics and techniques.
 </li>
 <li>
 Fine-tune models to improve predictive accuracy.
 
 
 </li>
 </ul>
 
 Data Visualization
 
 
 
 <ul>
 <li>
 Create informative data visualizations to communicate insights effectively.
 </li>
 <li>
 Work with visualization libraries like Matplotlib, Seaborn, or data visualization software&rsquo;s like Tableau, PowerBI.
 
 
 </li>
 </ul>
 
 Connect To Your Skills And Professional Experience.
 
 
 
 You're a Natural Problem Solver: Collaboration is at the core of our culture, and we're seeking someone who excels in teamwork and brings out the best in their colleagues. You'll be a brilliant listener, promoting a culture of innovation and knowledge sharing. At Deloitte, we believe in giving our AI/ML Engineers the autonomy they need to excel while upholding our high standards, integrity, and culture.
 
 
 
 Essentials
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Engineering or equivalent
 </li>
 <li>
 3-7 years of experience in Data Science and AI/ML
 </li>
 <li>
 Technical Expertise: Mastery in AI and ML algorithms, frameworks (e.g., TensorFlow, PyTorch), and libraries.
 </li>
 <li>
 Data proficiency: Proficient in data collection, pre-processing, and analysis.
 </li>
 <li>
 Model Mastery: Proven experience in developing and fine-tuning machine learning models.
 
 
 </li>
 </ul>
 
 Desirables
 
 
 
 <ul>
 <li>
 Familiarity with deploying ML frameworks in industry.
 </li>
 <li>
 A strong interest in staying abreast of the latest AI/ML advancements.
 </li>
 <li>
 Project Leadership: Previous experience leading AI/ML initiatives.
 
 
 </li>
 </ul>
 
 Connect to your service line - Technology and Transformation
 
 
 
 Distinctive thinking, deep expertise, and collaborative working. That&rsquo;s what connects us. That&rsquo;s what makes us Deloitte. If you want to help solve some of the biggest challenges around, join us. Together, we&rsquo;ll make an impact that matters.
 
 
 
 Our commitment to you
 
 
 
 Making an impact is more than just what we do: it&rsquo;s why we&rsquo;re here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before.
 
 
 We want you. The true you. Your own strengths, perspective, and personality. So, we&rsquo;re nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we&rsquo;ll take your wellbeing seriously, too. Because it&rsquo;s only when you&rsquo;re comfortable and at your best that you can make the kind of impact you, and we, live for.
 
 
 Your expertise is our capability, so we&rsquo;ll make sure it never stops growing. Whether it&rsquo;s from the complex work you do, or the people you collaborate with, you&rsquo;ll learn every day. Through world-class development, you&rsquo;ll gain invaluable technical and personal skills. Whatever your level, you&rsquo;ll learn how to lead.
 
 
 
 Connect to your next step
 
 
 
 A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you&rsquo;ll experience a purpose you can believe in and an impact you can see. You&rsquo;ll be free to bring your true self to work every day. And you&rsquo;ll never stop growing, whatever your level.
</div>

Deloitte Innovation Hub I Senior AI/ ML Engineer, Cairo, Egypt

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

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

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
 
 
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 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
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 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
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 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
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 </ul>
 
 Qualifications
 
 
 
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 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
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 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.
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Senior Machine Learning Engineer

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