llm engineer

MASTER-WORKS

<div>Design, develop, and deploy Arabic-first Large Language Model (LLM) solutions to support AI-driven products and client projects, ensuring high-quality Arabic language understanding, generation, and contextual accuracy across enterprises.
Key Responsibilities1. LLM Development &amp; NLP (Core)<ul><li>
Design and fine-tune LLMs for Arabic language tasks
</li><li><ul><li>Text generation, classification, summarization
</li><li>Arabic grammar correction, dialect handling
</li></ul></li><li>Build and optimize RAG pipelines
</li><li>Develop prompt engineering strategies for Arabic + English contexts
</li></ul>2. Data &amp; Arabic Language Engineering<ul><li>
Build and curate Arabic datasets
</li><li>Handle:
</li><li><ul><li>Dialects (Gulf, MSA, etc.)
</li><li>Data cleaning, normalization
</li></ul></li><li>Define evaluation benchmarks for Arabic LLM quality
</li></ul>3. AI System Architecture<ul><li>
Develop LLM-powered systems using:
</li><li><ul><li>LangChain / LangGraph / Llama / OpenAI APIs
</li><li>Vector databases (ChromaDB, FAISS, etc.)
</li></ul></li><li>Integrate LLMs into:
</li><li><ul><li>APIs
</li><li>Enterprise systems
</li><li>AI agents / copilots
</li></ul></li></ul>4. Production &amp; MLOps<ul><li>
Deploy scalable AI systems using:
</li><li><ul><li>Docker, Kubernetes
</li><li>Cloud platforms (Azure, AWS, GCP)
</li></ul></li><li>Optimize:
</li><li><ul><li>Latency
</li><li>Cost
</li><li>Throughput
</li></ul></li></ul>5. Cross-functional Collaboration<ul><li>
Work with:
</li><li><ul><li>PMs (scope, delivery, timelines)
</li><li>BAs (requirements translation AI logic)
</li><li>QA (model validation &amp; test cases)
</li></ul></li><li>Support client demos and AI solution design
</li></ul>6. Governance Alignment (Critical for Nabeh)<ul><li>
Ensure:
</li><li><ul><li>AI outputs align with client expectations
</li><li>Traceability (data model output)
</li></ul></li><li>Support:
</li><li><ul><li>BRD validation (AI feasibility)
</li><li>UAT and acceptance criteria</li></ul></li></ul> 

Requirements 
 
Required SkillsTechnical<ul><li>
Strong in:
</li><li><ul><li>Python (PyTorch / TensorFlow)
</li><li>NLP &amp; LLMs (Transformers, RAG)
</li></ul></li><li>Experience with:
</li><li><ul><li>LangChain / LLM frameworks
</li><li>Vector databases
</li><li>Prompt engineering
</li></ul></li></ul>Arabic AI (Mandatory)<ul><li>
Native or fluent Arabic
</li><li>Experience in:
</li><li><ul><li>Arabic NLP
</li><li>Dataset preparation for Arabic
</li><li>Handling dialects
</li></ul></li></ul>Engineering &amp; Deployment<ul><li>
APIs (FastAPI / Flask)
</li><li>Microservices architecture
</li><li>Docker, Kubernetes
</li><li>CI/CD pipelines</li></ul>
Language Requirements<ul><li>
Arabic: Native / Fluent (MANDATORY)
</li><li>English: Professional (MANDATORY)
</li></ul>Preferred Qualifications<ul><li>
MSc or higher in AI / Data Science / NLP
</li><li>Experience in:
</li><li><ul><li>Arabic LLMs (high priority)
</li><li>Government or enterprise AI projects
</li></ul></li><li>Certifications:
</li><li><ul><li>Azure AI / ML
</li><li>MLOps / Cloud certifications</li></ul></li></ul></div>

LLM Engineer - Arabic Speaker

GW Products

About GW ProductsGW Products is a fast-growing B2B trade hub powering brands, distributors, and retailers across North America with an AI-driven ERP and marketplace ecosystem built on Odoo. We&rsquo;re modernizing wholesale distribution with a connected platform that automates compliance, logistics, order flows, real-time analytics, AI assistants, marketplace features, and more , serving thousands of partners nationwide.As part of our engineering team, you&rsquo;ll help build next-generation ERP capabilities using Odoo and cutting-edge AI technologies (LLMs, RAG, intelligent agents) to redefine commerce systems at scale.What You&rsquo;ll DoAs an Odoo + AI / LLM Engineer, you will:Develop &amp; Enhance Odoo Modules<ul><li>Design, develop, and maintain custom Odoo modules tailored for marketplace, logistics, compliance, and AI-driven workflows.</li><li>Extend core Odoo functionality with scalable Python code, ORM enhancements, REST APIs, and efficient backend services.</li></ul>Build AI-Powered Features<ul><li>Integrate large language models and retrieval-augmented generation (RAG) pipelines into Odoo workflows.</li><li>Build and maintain intelligent AI agents that automate internal processes (e.g., intelligent assistants for support, compliance, insights).</li><li>Implement conversational interfaces, knowledge retrieval systems, and LLM-powered automation within the ERP ecosystem.</li></ul>Integrations &amp; Services<ul><li>Create robust integrations with external systems (3PL/4PL logistics, payment gateways, data sources, analytics systems, AI services).</li><li>Ensure secure and efficient webhook, API, and asynchronous patterns for real-time operations.</li></ul>Optimize &amp; Innovate<ul><li>Collaborate with product, data, and DevOps teams to optimize Odoo architecture, performance, and deployment workflows.</li><li>Be proactive in researching and adopting new AI/ML and automation technologies that bring measurable value.</li></ul>Ownership &amp; Impact<ul><li>Deliver clean, tested, and production-ready code with strong quality standards.</li><li>Help shape the technical direction of the AI + ERP integration layer for a marketplace platform used globally.</li></ul>Required Skills &amp; Experience<ul><li>Strong Odoo background (v14&ndash;v18 preferred) with proven experience building custom modules and workflows.</li><li>Python expert with deep understanding of Odoo ORM, APIs, and backend architecture.</li><li>Experience integrating external APIs, webhooks, async queues, and third-party services.</li><li>Practical experience using LLMs, RAG systems, or AI agent frameworks in production.</li><li>Comfortable with PostgreSQL, performance tuning, and scalable backend design.</li><li>Strong problem-solving ability with a proactive mindset.</li><li>Excellent collaboration skills across distributed teams.</li></ul>Nice-to-Have<ul><li>Familiarity with frameworks like LangChain, LlamaIndex, or similar for RAG/Agent systems.</li><li>Hands-on experience deploying LLMs and AI workflows in cloud environments.</li><li>Previous work on marketplace platforms, logistics/ERP systems, or high-growth SaaS products.</li></ul>Why You&rsquo;ll Love Working with Us<ul><li>Global Impact: Build technologies powering marketplaces and wholesale ERP used across the USA, EU, UAE, and beyond. gwproductsusa.com</li><li>Cutting-Edge Stack: Work at the intersection of Odoo + AI + Marketplace systems, shaping real product outcomes.</li><li>Remote &amp; Flexible: Work from anywhere &mdash; we value impact, not location.</li><li>Fast-Moving Team: Small teams, big opportunities, rapid delivery cycles.</li><li>Autonomy &amp; Ownership: Your ideas and code ship fast into production.</li></ul>Work Location: Remote

AI / LLM Engineer (RAG, Agents, Integrations)

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

Hustech

hustech.ai builds production-ready AI systems for real businesses. We work with international clients across automation, NLP, Computer Vision, LLM applications, and custom AI products. Our focus is delivery, reliability, and real business outcomes.Role OverviewWe are hiring an experienced Applied AI Engineer who can take ownership of client projects from start to finish.This is not a research-only role and not for fresh graduates. We need someone who can understand client requirements, design the right solution, build the system, deploy it, and support delivery.You should be comfortable handling different AI project types such as ML, Deep Learning, NLP, Computer Vision, LLM apps, RAG systems, and AI agents.What You&rsquo;ll Do<ul><li>Join client calls and convert requirements into technical solutions</li><li>Design end-to-end AI system architecture</li><li>Build and train ML / DL models</li><li>Develop NLP, CV, LLM, RAG, and agent-based systems</li><li>Build APIs and backend services using Python / FastAPI</li><li>Deploy solutions using Docker and cloud platforms</li><li>Integrate AI systems into client products and workflows</li><li>Optimize performance, accuracy, and scalability</li><li>Debug issues and deliver production-ready systems</li><li>Communicate progress clearly with international clients</li></ul>Required Experience<ul><li>3+ years professional industry experience (real client work, not coursework)</li><li>Proven experience delivering end-to-end AI projects</li><li>Strong Python skills</li><li>Hands-on experience in several of these areas: ML, DL, NLP, CV, LLMs, RAG, Agents etc</li><li>Experience with PyTorch or TensorFlow</li><li>Experience with APIs, FastAPI, Docker, deployment</li><li>Strong problem-solving and system design skills</li><li>Good spoken and written English</li><li>Comfortable speaking with international clients</li></ul>Preferred Skills<ul><li>AWS, GCP, or Azure</li><li>Vector databases (Qdrant, Pinecone, Weaviate)</li><li>OpenCV, Hugging Face, Scikit-learn</li><li>Automation tools and workflow systems</li></ul>Who Should ApplyApply only if you have already built and delivered real AI systems for companies or clients and can work independently with ownership.EducationBachelor&rsquo;s or Master&rsquo;s in Computer Science, AI, Machine Learning, or related field.Job Type: Full-timePay: Rs80,000.00 - Rs130,000.00 per monthExperience:<ul><li>AI Engineer: 3 years (Required)</li></ul>Language:<ul><li>English (Required)</li></ul>Work Location: In person

AI/ML Engineer

MVP Application and game design L.L.C

Role OverviewWe are looking for a highly skilled AI Agent &amp; Routing Engineer to design, build, and scale intelligent AI systems powered by LLMs. This role focuses on developing AI agents, orchestration layers, and routing logic that enable dynamic decision-making across multiple tools, models, and workflows.You will work on cutting-edge systems including AI agents, tool-use frameworks, multi-model routing, and MCP-based architectures, helping us build next-generation AI products.Key ResponsibilitiesAI Agents &amp; Orchestration<ul><li>Design and develop autonomous AI agents capable of reasoning, planning, and executing tasks</li><li>Implement tool-calling systems (APIs, functions, plugins, external services)</li><li>Build multi-step agent workflows with memory, context handling, and retries</li></ul>AI Routing Systems<ul><li>Develop intelligent AI routers that dynamically select:</li><li>Models (GPT, open-source, etc.)</li><li>Tools / APIs</li><li>Execution paths</li><li>Optimize routing based on latency, cost, and task complexity</li><li>Build fallback and failover logic across models and services</li></ul>MCP &amp; Integration<ul><li>Implement and integrate MCP (Model Context Protocol) for structured tool interaction</li><li>Design scalable agent-tool communication pipelines</li><li>Connect AI systems with internal and external services</li></ul>LLM Engineering<ul><li>Work with LLM APIs and frameworks (OpenAI, open-source models, etc.)</li><li>Implement prompt engineering, structured outputs, and guardrails</li><li>Handle context windows, embeddings, and retrieval workflows</li></ul>Backend Development<ul><li>Build scalable backend services using Node.js or Python</li><li>Design APIs for agent orchestration and routing</li><li>Ensure performance, reliability, and observability</li></ul>RequirementsMust-Have<ul><li>Strong experience in JavaScript (Node.js) or Python</li><li>Experience building AI agents or LLM-powered applications</li><li>Understanding of:</li><li>Function/tool calling</li><li>Prompt engineering</li><li>Multi-step workflows</li><li>Experience with AI routing / orchestration logic</li><li>Familiarity with MCP (Model Context Protocol) or similar architectures</li></ul>Nice to Have<ul><li>Experience with frameworks like:</li><li>LangChain / LlamaIndex / custom agent frameworks</li><li>Knowledge of:</li><li>Vector databases (Pinecone, Weaviate, etc.)</li><li>RAG systems</li><li>Experience with multi-model systems (OpenAI + open-source)</li><li>DevOps experience (Docker, cloud deployment, scaling AI workloads)</li></ul>What You&rsquo;ll Build<ul><li>AI agent systems that think, decide, and act autonomously</li><li>Smart routers that choose the best model/tool per request</li><li>MCP-based ecosystems connecting AI to real-world tools</li><li>Production-grade AI infrastructure used by thousands of users</li></ul>Ideal Candidate<ul><li>Thinks like a system designer, not just a coder</li><li>Obsessed with AI architecture and performance optimization</li><li>Can turn vague ideas into working intelligent systems</li><li>Comfortable working in fast-moving, experimental environments</li></ul>Why Join Us<ul><li>Work on cutting-edge AI systems (agents, routing, orchestration)</li><li>High ownership and impact on core product architecture</li><li>Opportunity to shape the future of AI products in the region</li></ul>Job Type: Full-timePay: AED4,000.00 - AED5,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>AI Agent &amp; Routing Engineer: 1 year (Required)</li><li>Software Development: 3 years (Required)</li></ul>Language:<ul><li>English (Required)</li></ul>Work Location: In person

AI Agent Developer

Greenfield Marine Technologies

We are looking for a hands-on GenAI Engineer to design, build, and deploy production-grade AI applications powered by Large Language Models (LLMs). This role is focused on turning business use cases into reliable, scalable AI solutions such as copilots, knowledge assistants, document intelligence tools, and workflow automation systems.The ideal candidate combines strong software engineering skills with practical experience in LLM application development, Retrieval-Augmented Generation (RAG), prompt engineering, model evaluation, and API integration. This person should be comfortable moving from prototype to production while optimizing for quality, latency, security, and cost. This builds on the original JD&rsquo;s emphasis on LLM apps, RAG, integrations, vector databases, and cloud deployment.Key Responsibilities:<ul><li>Design, develop, and deploy GenAI applications using LLMs for real-world business workflows.</li><li>Build AI-powered solutions such as chatbots, copilots, knowledge assistants, search assistants, and workflow automation tools</li><li>Architect and optimize RAG pipelines using structured and unstructured enterprise data.</li><li>Develop robust prompt strategies, guardrails, and response orchestration for accuracy and safety.</li><li>Integrate AI capabilities into web applications, backend systems, APIs, and enterprise platforms.</li><li>Work with vector databases and retrieval systems to improve relevance and response quality.</li><li>Evaluate model performance using defined quality metrics, test cases, and user feedback loops.</li><li>Improve production performance across latency, cost, scalability, observability, and reliability.</li><li>Collaborate with product, engineering, and business teams to translate use cases into deployable AI features.</li><li>Stay updated with emerging GenAI tools, frameworks, and model capabilities, and recommend practical adoption where relevant.</li></ul>Must-Have Skills: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Strong hands-on programming experience in Python. Experience building GenAI applications using frameworks such as LangChain, LlamaIndex, or equivalent orchestration tools. Experience working with OpenAI APIs, Anthropic, Bedrock, Azure OpenAI, or similar LLM platforms. Strong understanding of prompt engineering, RAG architecture, and LLM application design. Experience integrating AI models with REST APIs, web applications, and backend services. Familiarity with vector databases such as FAISS, Pinecone, Weaviate, Chroma, or similar. Good understanding of machine learning and NLP fundamentals.Experience deploying production-ready applications on AWS, Azure, or GCP.Ability to evaluate and improve model quality, including hallucination reduction and retrieval performance.Understanding of security, access control, and safe handling of enterprise data in AI applications.Preferred Skills : Experience with Amazon Bedrock. Experience with multimodal AI applications involving text, images, PDFs, and document processing. Familiarity with fine-tuning, adapters, or domain adaptation techniques for LLMs.Experience with Docker, Kubernetes, CI/CD pipelines, and MLOps workflows.Exposure to observability and monitoring tools for AI systems.Experience building domain-specific assistants for operations, compliance, technical support, or enterprise knowledge systems.Experience Required:2&ndash;3 years of experience in software engineering, machine learning, or AI application development.At least 1&ndash;2 years of practical experience working on GenAI / LLM-based applications in production or advanced PoCs.Job Types: Full-time, PermanentAbility to commute/relocate:<ul><li>Abu Dhabi: Reliably commute or planning to relocate before starting work (Required)</li></ul>Application Question(s):<ul><li>What is your Visa Status?</li><li>What is your Current Salary?</li><li>What is your Expected Salary?</li><li>Visa Expiry Date?</li><li>Duration of Notice Period?</li><li>Mention your available dates for an online interview</li></ul>Experience:<ul><li>GenAI: 2 years (Required)</li></ul>Location:<ul><li>Abu Dhabi (Required)</li></ul>Work Location: In person

GenAI Engineer

Confiz

<div>We are seeking an exceptional Senior AI Engineer to join our team and drive the development of cutting-edge AI solutions that includes conversational, Agentic AI's. This role focuses on building advanced conversational AI systems, implementation AI Agents across different use cases, implementing sophisticated RAG architectures, and deploying production-grade voice AI applications. The ideal candidate will have deep expertise in LLM technologies and a proven track record of delivering scalable AI solutions.
Key Responsibilities
<ul><li>Design and implement advanced Retrieval-Augmented Generation (RAG) systems with sophisticated chunking strategies, multi-vector retrieval, and hybrid search architectures</li>
<li>Develop and optimize conversational AI agents with complex multi-turn dialogue management and context awareness</li>
<li>Build production-ready voicebot solutions integrating real-time speech processing pipelines</li>
<li>Architect and deploy Text-to-Speech (TTS) and Speech-to-Text (STT) systems with low latency and high accuracy</li>
<li>Design and Deploy PROD grade AI Agents that can scale up for various use cases.</li>
<li>Fine-tune large language models using various techniques.</li>
<li>Optimize model performance through prompt engineering, few-shot learning, and retrieval strategies</li>
<li>Implement evaluation frameworks and metrics for LLM outputs and conversational quality</li>
<li>Develop custom training pipelines for domain adaptation and specialized use cases</li>
<li>Design scalable AI infrastructure supporting real-time inference and high-throughput batch processing</li>
<li>Implement efficient vector databases and semantic search systems (Pinecone, Azure Search)</li>
<li>Build monitoring and observability solutions for AI systems in production</li>
<li>Stay current with latest developments in LLM architectures, RAG techniques, and voice AI technologies</li>
<li>Experiment with emerging models and frameworks to evaluate applicability to business problems</li>
<li>Contribute to technical documentation, best practices, and knowledge sharing within the team</li>
<li>Prototype and validate new AI capabilities through POCs and pilots</li>
</ul>
Required Qualifications
<ul><li>8+ years of software engineering experience with 4+ years focused on AI/ML engineering</li>
<li>Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)</li>
<li>Master's or PhD in Computer Science, AI/ML, or related technical field</li>
<li>Experience with open-source LLMs (Llama, Mistral, etc.) and local deployment</li>
<li>Knowledge of reinforcement learning from human feedback (RLHF) and DPO</li>
<li>Familiarity with multi-modal AI systems (vision-language models, audio-visual understanding)</li>
<li>Experience with real-time streaming architectures and WebRTC</li>
<li>Published research or contributions to open-source AI projects</li>
<li>Experience with GPU optimization and distributed training</li>
<li>Knowledge of voice biometrics, speaker diarization, or emotion recognition</li>
<li>Background in linguistics, phonetics, or speech processing</li>
<li>Deep hands-on experience with advanced RAG systems:</li>
<li>Multi-stage retrieval architectures (hybrid search, re-ranking)</li>
<li>Embedding models and vector similarity search</li>
<li>Document processing, chunking strategies, and metadata filtering</li>
<li>Query understanding and retrieval optimization</li>
<li>Multi-turn dialogue management</li>
<li>Intent recognition and slot filling</li>
<li>Context tracking and memory management</li>
<li>Integration with LLM APIs (OpenAI, Anthropic, Cohere, etc.)</li>
<li>Production experience with voicebot development:</li>
<li>Real-time audio streaming and processing</li>
<li>Voice activity detection (VAD)</li>
<li>End-to-end latency optimization</li>
<li>Integration of STT, dialogue management, and TTS components</li>
<li>Expertise in TTS and STT technologies:</li>
<li>Modern TTS systems (ElevenLabs, Soniox, Azure Speech)</li>
<li>STT engines ( Deepgram, AssemblyAI)</li>
<li>Audio preprocessing and enhancement</li>
<li>Voice cloning and customization</li>
<li>Strong experience with LLM fine-tuning:</li>
<li>Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)</li>
<li>Experience with MLOps tools and practices (MLflow, Weights &amp; Biases, experiment tracking)</li>
<li>Strong understanding of API design, microservices architecture, and system integration</li>
<li>Knowledge of version control, CI/CD pipelines, and deployment automation</li>
</ul>
We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM), ISO 14001:2015 (EMS), ISO 45001:2018 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/</div>

AI Architect

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