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Qureos

AI Engineer Company:** Qureos Location:** Karachi, Pakistan Employment Type:** Full-Time About Qureos Qureos is a dynamic and forward-thinking organisation dedicated to shaping the future of career development. We are committed to empowering professionals by connecting them with meaningful opportunities, mentorship, and the skills needed to thrive in a competitive landscape. Our innovative platform leverages technology to bridge the gap between talent and industry, and we are now seeking a talented AI Engineer to join our pioneering team. Job Overview We are looking for a highly skilled and motivated AI Engineer to join our team in Karachi. The ideal candidate will be passionate about artificial intelligence and its application in solving real-world challenges. You will play a crucial role in designing, developing, and deploying cutting-edge AI and machine learning models that power our platform's core features, from intelligent job matching and skill analysis to personalised career guidance. This is an exciting opportunity to make a significant impact within a growing company at the forefront of the EdTech and recruitment industries. Responsibilities - Design, build, and deploy robust machine learning models to enhance our platform's capabilities. - Develop and refine recommendation systems to accurately match candidates with relevant job opportunities, projects, and mentors. - Utilise Natural Language Processing (NLP) techniques to analyse and interpret data from resumes, job descriptions, and user interactions. - Collaborate with cross-functional teams, including software engineers, product managers, and data scientists, to integrate AI solutions into our products. - Manage the end-to-end lifecycle of AI models, including data collection, preprocessing, training, evaluation, and deployment. - Stay current with the latest advancements in AI, machine learning, and deep learning to drive continuous innovation. - Ensure the ethical and responsible use of AI, maintaining fairness and avoiding bias in all models. - Optimise AI models for performance, scalability, and efficiency. Qualifications - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field. - Proven commercial experience as an AI Engineer, Machine Learning Engineer, or in a similar role. - Strong programming proficiency in Python and extensive experience with key AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn. - Solid understanding of machine learning algorithms, deep learning, NLP, and statistical modelling. - Experience with data processing and analysis using tools like Pandas and NumPy. - Familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) and MLOps practices is highly desirable. - Excellent problem-solving abilities and a creative, analytical mindset. - Strong communication skills and the ability to work effectively in a collaborative team environment. Benefits - A competitive salary and comprehensive benefits package. - Opportunities for professional development and continuous learning. - A vibrant and supportive work culture that encourages innovation and collaboration. - The chance to work on meaningful projects that directly impact people's careers. - Flexible and modern working environment.

AI Engineer

Digitrends

AI EngineerKey Responsibilities<ul><li>Design, develop, and fine-tune LLM-based AI models for real-world applications.</li><li>Implement custom LLM training, reinforcement learning, and fine-tuning using open-source and proprietary models like GPT, Llama, Mistral, Claude, or Falcon.</li><li>Optimize model efficiency, inference speed, and resource utilization for deployment in cloud or on-premise environments.</li><li>Build data pipelines for training and evaluating AI models.</li><li>Implement prompt engineering, retrieval-augmented generation (RAG), and memory-based techniques for improved performance.</li><li>Integrate LLMs into applications using APIs, LangChain, vector databases (e.g., Pinecone, FAISS, ChromaDB).</li><li>Develop custom embeddings, transformers, and tokenization strategies for specific use cases.</li><li>Work closely with MLOps, backend engineers, and data scientists to ensure smooth deployment and monitoring of AI solutions.</li><li>Research and stay updated on emerging trends in NLP, generative AI, and model compression techniques.</li><li>Ensure compliance with ethical AI principles and data security standards when handling sensitive data.</li></ul>Required Skills:<ul><li>Strong knowledge of Python and frameworks like PyTorch, TensorFlow, JAX.</li><li>Experience with Hugging Face Transformers, OpenAI API, LangChain, and vector databases.</li><li>Understanding of LLM architectures, fine-tuning techniques (LoRA, QLoRA, PEFT), and model distillation.</li><li>Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).</li><li>Familiarity with distributed computing, GPU acceleration (CUDA, TensorRT), and multi-node training.</li><li>Knowledge of AI safety, bias mitigation, and responsible AI development.</li><li>Strong problem-solving, debugging, and optimization skills.</li><li>Excellent communication and teamwork skills.</li></ul>Preferred Qualifications<ul><li>Experience in building domain-specific AI assistants or chatbots.</li><li>Knowledge of multimodal AI, speech-to-text, text-to-image models.</li><li>Contributions to open-source AI projects or research papers in NLP/LLMs.</li></ul>Key Benefits<ul><li>Working in a fast-paced tech start-up environment</li><li>Attractive salary and incentives for high-quality work</li><li>Flexible schedule</li><li>Health Insurance</li><li>Five Working Days</li><li>Provident Fund</li></ul>Job Type: Full-timeWork Location: In person

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>5+ 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>

Senior AI Engineer

LeadingEdge HR Solutions

<div>
 
 NOW HIRING | SENIOR AI ENGINEER &ndash; REMOTE | BAHRAIN
 
 
 
 
 Position Title:
 
 Senior AI Engineer
 
 
 
 Location:
 
 Bahrain (Remote)
 
 
 
 Contract Type:
 
 Full-Time Permanent
 
 
 
 Role Overview
 
 
 
 Our Client is a forward-thinking organisation based in Bahrain, operating at the intersection of technology and financial services. They are seeking a skilled
 
 Senior AI Engineer
 
 to
 
 design, develop, and deliver end-to-end AI solutions
 
 &mdash; bringing a strong
 
 consultancy or banking background
 
 and the ability to translate complex business challenges into scalable, production-ready AI applications on a fully
 
 remote basis.
 
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and deploy end-to-end AI use cases that are directly aligned to business objectives and organisational priorities.
 </li>
 <li>
 Engage with business stakeholders across consulting and banking functions to identify, scope, and prioritise AI opportunities with measurable impact.
 </li>
 <li>
 Translate complex operational and business requirements into intelligent, production-ready AI and machine learning solutions.
 </li>
 <li>
 Build, optimise, and maintain machine learning models, data pipelines, and AI-driven applications to the highest technical standards.
 </li>
 <li>
 Ensure all AI solutions are robust, scalable, and suitable for live production environments.
 </li>
 <li>
 Continuously monitor industry developments, emerging AI tools, and evolving best practices within the banking and consulting sectors.
 </li>
 <li>
 Clearly document technical processes, methodologies, and outcomes; present findings to both technical teams and senior non-technical stakeholders.
 
 
 
 </li>
 </ul>
 
 Required Experience &amp; Skills
 
 
 
 <ul>
 <li>
 Minimum 2 years of hands-on experience in designing, building, and deploying AI and machine learning solutions.
 </li>
 <li>
 Demonstrated ability to deliver end-to-end AI projects independently from concept through to full production deployment.
 </li>
 <li>
 Prior experience within consulting and/or banking and financial services is strongly preferred.
 </li>
 <li>
 Strong proficiency in Python with practical experience across leading AI tools, machine learning libraries, and development frameworks.
 </li>
 <li>
 Proven working knowledge of cloud platforms including AWS, Microsoft Azure, or Google Cloud.
 </li>
 <li>
 Solid experience working with large-scale datasets and building predictive or natural language processing models.
 </li>
 <li>
 Exceptional communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
 </li>
 <li>
 Highly self-managed, organised, and dependable in a fully remote working environment.
 
 
 
 </li>
 </ul>
 
 Apply Now:
 
 
 
 
 Interested candidates can share there resume at
 
 talent@leadingedge.plus
 
 mentioning title in the subject line.
 
</div>

SENIOR AI ENGINEER – ONSITE_KHI

DM Clinical Research

<div>We are seeking an AI Applications Engineer with deep expertise in AI systems development to join our engineering team. In this role, you&rsquo;ll bridge the gap between ML research and real-world software delivery &mdash; designing, developing, and deploying intelligent applications powered by modern AI technologies including LLMs, multimodal models, and agentic workflows. You'll work closely with data scientists, ML engineers, and product managers to ship cutting-edge, scalable AI-powered features across web, backend, and mobile platforms. 
DUTIES &amp; RESPONSIBILITIES<ul><li>
Design and build AI-native applications leveraging LLMs (e.g., OpenAI, Anthropic, Mistral) and multimodal models.</li><li>
Architect and implement agent-based workflows using frameworks like LangGraph, CrewAI, and AutoGen.</li><li>
Develop production-grade Python services using FastAPI or similar frameworks to expose AI functionalities via APIs.</li><li>
Fine-tune and serve custom LLMs for text, voice, and multimodal inputs; implement Retrieval-Augmented Generation (RAG) pipelines.</li><li>
Integrate vector search systems (e.g., Weaviate, Qdrant, Pinecone) for semantic memory and contextual reasoning.</li><li>
Use modern orchestration tools like LangChain, Flowise, Haystack, or n8n to prototype and scale intelligent flows.</li><li>
Leverage the OpenAI Function Calling / Tools API and Model Context Protocol (MCP) to build structured, dynamic LLM interactions.</li><li>
Implement continuous evaluation loops using synthetic data, human feedback (RLHF), and evaluation frameworks like Ragas or DeepEval.</li><li>
Collaborate with ML/infra teams to containerize, deploy, and monitor models using tools like Docker, MLflow, BentoML, or Kubernetes.</li><li>
Build scalable, secure, and efficient AI feature delivery pipelines across web and mobile platforms.</li><li>
Stay current with developments in foundation models, agent frameworks, multimodal AI, and open-source toolkits.</li></ul>
KNOWLEDGE &amp; EXPERIENCE
Education:<ul><li>
Bachelor's or Master&rsquo;s degree in Computer Science, Software Engineering, Artificial Intelligence, or related discipline.</li></ul>
Experience:<ul><li>
2&ndash;4 years of experience building and deploying AI/ML-powered software.</li><li>
Proven track record of delivering LLM-integrated applications and/or agentic workflows in production.</li><li>
Experience in any of the following domains is a plus: NLP, computer vision, multimodal models, or conversational AI.</li></ul>
Knowledge and Skills:<ul><li>
Proficient in Python and building production-grade RESTful APIs (FastAPI preferred).</li><li>
Experience working with foundation model APIs (OpenAI, Claude, Gemini, Mistral, Cohere).</li><li>
Familiarity with LangChain, LangGraph, CrewAI, Flowise, or similar frameworks.</li><li>
Experience implementing RAG pipelines and retrieval layers with vector databases (Pinecone, Qdrant, Weaviate, FAISS).</li><li>
Understanding of prompt engineering, structured memory (MCP), tool calling, and multi-turn conversation flows.</li><li>
Comfortable with tools like MLflow, Weights &amp; Biases, or BentoML for model versioning and tracking.</li><li>
Ability to integrate with third-party services, RESTful APIs, and webhooks (Zapier, n8n, etc.).</li><li>
Familiarity with MLOps and CI/CD workflows for AI applications.</li><li>
Experience working with containerized environments (Docker, Kubernetes).</li><li>
Git, agile software development practices, and collaborative code workflows.</li><li>
Experience with speech recognition (Whisper), text-to-speech (ElevenLabs), or multimodal APIs (e.g., GPT-4o).</li></ul></div>

AI Applications Engineer

NorthBay Solutions

<div>
 
 
 Role: Team Lead - Azure AI (Agentic) Engineer
 
 
 
 
 Location:
 
 Pakistan (hybrid work model)
 
 
 
 
 Client: Middle East (Government)
 
 
 
 
 
 
 About the Role:
 
 
 
 
 NorthBay Solutions, an AWS global Consulting Partner with distributed teams across the US, Canada, UAE, India, and Pakistan, is hiring a high-caliber&nbsp;
 
 Azure AI Specialist (Team Lead)
 
 with deep expertise in building enterprise-grade
 
 Generative AI, RAG, and Agentic AI solutions
 
 on the Azure ecosystem.
 
 
 This role requires hands-on experience in designing scalable, multi-tenant AI systems, integrating LLMs, and building intelligent pipelines using Azure-native services.
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design and deploy
 
 LLM-powered applications
 
 using Azure OpenAI for enterprise use cases
 </li>
 <li>
 Build and optimize
 
 Retrieval-Augmented Generation (RAG)
 
 pipelines using Azure AI Search (vector + hybrid search)
 </li>
 <li>
 Develop
 
 Agentic AI systems
 
 leveraging frameworks and tool-based reasoning approaches
 </li>
 <li>
 Implement
 
 custom Document Intelligence models
 
 for high-accuracy data extraction (e.g., IDs, structured documents)
 </li>
 <li>
 Architect
 
 multi-tenant AI deployments
 
 with scalability, security, and cost-efficiency in mind
 </li>
 <li>
 Develop and manage
 
 Knowledge Graphs
 
 for structured reasoning and contextual intelligence
 </li>
 <li>
 Apply advanced
 
 prompt engineering techniques
 
 (Few-shot, Chain-of-Thought, ReAct)
 </li>
 <li>
 Use
 
 Prompt Flow in Azure AI Studio
 
 for experimentation, testing, and versioning
 </li>
 <li>
 Design
 
 intelligent conversational systems
 
 with fallback handling and contextual memory
 </li>
 <li>
 Build and manage
 
 MLOps pipelines
 
 using Azure Machine Learning
 </li>
 </ul>
 
 
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 Overall 10+ years experience, with a focus on&nbsp;
 
 Azure OpenAI API
 
 (deployments, scaling, optimization)
 </li>
 <li>
 Proven expertise in building
 
 RAG pipelines using Azure AI Search
 
 </li>
 <li>
 Experience with
 
 vector databases and hybrid search architectures
 
 </li>
 <li>
 Practical experience in
 
 Agentic AI / multi-agent systems
 
 </li>
 <li>
 Hands-on with
 
 Azure AI Document Intelligence (Form Recognizer)
 
 </li>
 <li>
 Solid understanding of
 
 Knowledge Graphs and semantic modeling
 
 </li>
 <li>
 Expertise in
 
 prompt engineering &amp; LLM optimization techniques
 
 </li>
 <li>
 Experience with
 
 Prompt Flow (Azure AI Studio)
 
 </li>
 <li>
 Strong background in
 
 Python and cloud-native development
 
 </li>
 <li>
 Experience with
 
 Azure ML / MLOps pipelines
 
 </li>
 <li>
 Ability to design scalable and secure
 
 enterprise AI architectures
 
 </li>
 </ul>
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience with
 
 LangChain, Semantic Kernel, or similar frameworks
 
 </li>
 <li>
 Exposure to
 
 multi-agent orchestration tools
 
 </li>
 <li>
 Prior experience working with
 
 enterprise clients or large-scale AI deployments
 
 </li>
 </ul>
</div>

Azure AI (Agentic) Specialist - Team Lead

The Ghani IT Solutions

Role Overview:We are seeking a Senior AI Engineer to architect and build a high-performance, custom Voice AI infrastructure. This role focuses on developing an end-to-end real-time audio processing pipeline and an intelligent NLP engine capable of synthesizing complex regulatory data into actionable insights with sub-second latency.Key Responsibilities:- Custom Voice Infrastructure: Develop a proprietary, low-latency audio pipeline integrating Speech-to-Text (STT), Large Language Models (LLMs), and Text-to-Speech (TTS).- Intelligent Data Parsing: Architect agentic workflows to ingest complex documentation and translate technical/legal jargon into plain-language summaries.- Real-time Audio Streaming: Manage full-duplex audio transmission using WebSockets and WebRTC to achieve human-like conversational responsiveness.- Automated Information Retrieval: Build scalable scrapers and API consumers to monitor high-frequency data sources and public registries for real-time updates.- Advanced RAG Systems: Implement sophisticated Retrieval-Augmented Generation (RAG) using Vector Databases to provide the AI with deep contextual awareness.Technical Requirements:- Programming: Expert-level Python; experience with asynchronous programming and high-concurrency systems.- NLP &amp; AI: Proven experience with LangChain, LlamaIndex, and fine-tuning open-source LLMs.- Speech Processing: Experience with real-time transcription (STT) and neural speech synthesis (TTS) engines.- Data Systems: Proficiency with Vector DBs (e.g., Pinecone, Milvus) and SQL/NoSQL databases.- Protocols: Strong understanding of WebSockets, WebRTC, and real-time data streaming.Location: DHA Phase 6, KarachiShift: MorningWork Location: In person

Senior AI & Machine Learning Engineer (Speech & NLP Specialist)

Explore 243+ Ai engineer in Karachi this April. Find roles across top companies and apply now to boost your career.

243 ai engineer jobs In Karachi

AI Engineer

AI Engineer

Senior AI Engineer

SENIOR AI ENGINEER – ONSITE_KHI

AI Applications Engineer

Azure AI (Agentic) Specialist - Team Lead

Senior AI & Machine Learning Engineer (Speech & NLP Specialist)