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ai/ml engineer

nlp engineer

Simcoe IT

We are looking for a motivated AI Engineer / API Integrator to join our growing AI development team. The ideal candidate will have hands-on experience in Python, API integration, and LangChain frameworks. You will be responsible for connecting and optimizing external AI and NLP APIs to power next-generation, multi-modal AI solutions.Key Responsibilities<ul><li>Integrate and manage external AI and NLP APIs within the AI Processing Router Engine.</li><li>Design and maintain query routing pipelines for text, image, and video workflows.</li><li>Test and optimize API performance and latency across different AI layers.</li><li>Handle API token management, authentication, and security.</li><li>Collaborate with backend engineers to ensure stable and scalable integration.</li></ul>Required Skills &amp; Experience<ul><li>2 years of hands-on experience with Python programming.</li><li>Solid understanding of LangChain, LLM workflows, and prompt optimization.</li><li>Proven ability in API integration (REST / GraphQL) and data handling.</li><li>Familiarity with AI model deployment and multi-modal (text / image / video) data routing.</li><li>Strong debugging, analytical, and documentation skills.</li></ul>Apply at: haroon@searchopal.com Or share CV via WhatsApp: 0337-9928258Job Type: Full-timePay: Rs80,000.00 - Rs90,000.00 per monthWork Location: In person

AI Engineer / API Integrator

ibex

<div>
 We are seeking a highly skilled and creative
 
 AI Agent Conversation Designer/Engineer
 
 to join our team and help shape the next generation of customer experience through intelligent virtual agents. This role sits at the intersection of
 
 conversation design, user experience, AI/NLP technologies, and CX strategy
 
 . You will be responsible for crafting natural, engaging, and effective conversations for AI-powered customer service bots, and for building the logic, flows, and backend integrations that power them.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and optimize conversational experiences across text, voice, and multimodal AI agents that serve customer-facing use cases.
 </li>
 <li>
 Collaborate with CX, product, and engineering teams to define intents, utterances, and dialogue flows aligned to business goals and customer needs.
 </li>
 <li>
 Use tools such as Dialogflow, Microsoft Bot Framework, Rasa, Kore.ai, or proprietary platforms to develop, test, and deploy virtual agents.
 </li>
 <li>
 Write natural, human-like copy that reflects brand voice while supporting task completion, escalation, and error handling.
 </li>
 <li>
 Analyze conversational data to continuously improve agent performance&mdash;tuning intents, training datasets, and optimizing flows.
 </li>
 <li>
 Integrate back-end systems and APIs to allow bots to handle dynamic requests (e.g., checking account status, processing returns, scheduling).
 </li>
 <li>
 Develop test cases and perform QA to ensure smooth, bug-free performance in production environments.
 </li>
 <li>
 Stay up to date with NLP, LLMs, and conversational AI innovations to inform ongoing development and optimization.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Linguistics, UX Design, Human-Computer Interaction, AI, or a related field. Or equivalent on the job experience
 </li>
 <li>
 3+ years of experience in conversation design, chatbot development, or NLP engineering.
 </li>
 <li>
 Proficiency in one or more bot development platforms: Google Dialogflow, AWS Lex, Rasa, Kore.ai, Cognigy, etc.
 </li>
 <li>
 Familiarity with programming languages (e.g., Python, JavaScript) and basic API integration.
 </li>
 <li>
 Understanding of machine learning and natural language understanding (NLU) principles.
 </li>
 <li>
 Strong grasp of UX best practices, persona development, and user-centric design.
 </li>
 <li>
 Experience with LLM integration and prompt engineering (e.g., OpenAI, Anthropic, Cohere) is a strong plus.
 </li>
 <li>
 Excellent problem-solving, collaboration, and communication skills.
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 
 
 <ul>
 <li>
 Experience designing for voice assistants (e.g., Alexa, Google Assistant).
 </li>
 <li>
 Knowledge of analytics platforms (e.g., Voiceflow, Dashbot, Botanalytics) for bot performance tracking.
 </li>
 <li>
 Familiarity with customer service domains such as e-commerce, telecom, healthcare, or fintech.
 </li>
 <li>
 Background in multilingual or multicultural experience design.
 </li>
 </ul>
</div>

AI Conversation Designer

Contegris Pvt Ltd

About ContegrisContegris is a leading SaaS company dedicated to delivering Technology Solutions for a Delightful Customer Experience. Since 2012, weve been empowering over 300 enterprise clients across 20+ industries with our smart and scalable solutions. Our product suite includes an Omni-Channel Contact Center Platform (Intellicon), Helpdesk, Sales CRM, Unified Communication, WhatsApp Business API, and AI-powered self-service tools. With innovation at the core, we strive to enhance how businesses connect with their customers.Job Overview:We are seeking a motivated and detail-oriented AI Engineer to support the development, enhancement, and maintenance of our AI-driven products. The ideal candidate will have a strong foundation in machine learning, LLMs, AI tooling, and modern development practices. They must be able to understand existing codebases, debug issues, implement new features, and collaborate with the team to improve our AI systems. This role requires the ability to work with AI coding assistants (e.g., Claude), but with a solid understanding of the underlying logic, architecture, and algorithms to ensure code quality and maintainability.Key Responsibilities:<ul><li>Develop new features for our AI products across multiple modules and components.</li><li>Understand the architecture, workflows, and logic behind existing AI systems.</li><li>Debug issues, investigate model behavior, and provide support for already deployed AI features.</li><li>Enhance and improve existing AI functionalities to increase performance, accuracy, and scalability.</li><li>Use Claude as a development assistant while maintaining complete ownership and understanding of all produced code.</li><li>Integrate and fine-tune LLMs and AI tools based on product needs.</li><li>Collaborate with Product, QA, and Development teams to deliver high-quality releases.</li><li>Write clean, efficient, and well-documented code following engineering best practices.</li><li>Stay updated with the latest AI tools, frameworks, models, and industry trends.</li></ul>Qualification<ul><li>Strong foundational knowledge of Machine Learning, NLP, and LLM (Large Language Model) concepts.</li><li>1-2 years of experince working as AI Engineer</li><li>Hands-on experience with Python and common AI/ML libraries (TensorFlow, PyTorch, HuggingFace, LangChain, etc.).</li><li>Understanding of prompt engineering, retrieval-augmented generation (RAG), vector databases, and embeddings.</li><li>Ability to work with APIs (OpenAI, Anthropic Claude, Google GenAI, etc.).</li><li>Solid debugging and problem-solving skills for AI applications.</li><li>Familiarity with cloud platforms (AWS, GCP, Azure) is a plus.</li><li>Understanding of version control (Git) and CI/CD workflows.</li><li>Ability to read, understand, and refactor code written with AI assistance tools.</li></ul>Preferred Tools &amp; Technologies<ul><li>LLMs &amp; AI Platforms: Claude, OpenAI GPT, HuggingFace, Google Vertex AI</li><li>Vector Databases: Pinecone, Weaviate, Milvus, Qdrant</li><li>Frameworks &amp; Libraries: LangChain, LlamaIndex, Transformers</li><li>ML Tools: Jupyter, Pandas, NumPy, Scikit-learn</li><li>DevOps &amp; Deployment: Docker, Linux basics, NGINX, FastAPI/Flask</li><li>Other Tools: Redis, MongoDB, ElasticSearch (optional)</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>Expected Salary </li></ul>Work Location: In person

AI Engineer

Techeezy

Company: SparkAiExperience: 4 to 5 yearsEmployment Type: Full-timeLocation: LahoreRole Overview:We are looking for a highly skilled Senior Python Developer with expertise - in Generative AI and Retrieval-Augmented Generation (RAG). The ideal candidate should have hands-on experience in LLMs, prompt engineering, vector databases, and AI-driven application development.Key Responsibilities<ul><li>Familiarity with Graph Databases like Neo4j</li><li>Develop and optimize LLM-powered applications using Python.</li><li>Implement Retrieval-Augmented Generation (RAG) pipelines for AI-driven search and content generation.</li><li>Design and fine-tune prompt engineering strategies for better AI responses.</li><li>Integrate OpenAI, LangChain, Hugging Face, and other AI frameworks into scalable applications.</li><li>Optimize ML models and deployments using Docker, FastAPI, Flask, and other frameworks.</li><li>Collaborate with cross-functional teams to deliver AI-powered solutions.</li></ul>Requirements<ul><li>Experience in LLMs, OpenAI API, LangChain, Hugging Face</li><li>Proficiency in RAG</li><li>Understanding of NLP, embeddings, and knowledge graphs</li><li>Familiarity with cloud services (AWS, GCP, Azure)</li><li>Experience in API development (FastAPI, Flask, Django, Rest)</li><li>Knowledge of MLOps &amp; model deployment is a plus</li></ul>Please fill this form https://forms.gle/9d8XndUBqMtoZ5u18Job Type: Full-timeWork Location: In person

Sr. Python Developer

Expert System Solution

About the RoleWe are seeking a Senior AI/ML Engineer with strong technical expertise and exceptional communication skills. The ideal candidate must be a closer, someone who can take ownership, deliver results, and confidently drive AI/ML solutions from concept to deployment.Key Responsibilities<ul><li>Design, develop, and deploy end-to-end AI/ML models and data pipelines.</li><li>Build predictive models, NLP solutions, and deep learning architectures.</li><li>Collaborate with cross-functional teams to understand business needs and deliver practical AI solutions.</li><li>Optimize model performance, scalability, and accuracy.</li><li>Conduct research on latest AI trends and implement relevant advancements.</li><li>Present findings, models, and results clearly to technical and non-technical stakeholders.</li><li>Lead critical problem-solving discussions and ensure timely closure of tasks.</li></ul>Requirements<ul><li>4+ years of hands-on experience in Machine Learning, AI model development, and data engineering.</li><li>Strong expertise in Python, TensorFlow/PyTorch, Scikit-Learn, NLP, Deep Learning, and Cloud (AWS/GCP/Azure).</li><li>Solid understanding of data structures, algorithms, statistical modeling, and MLOps frameworks.</li><li>Proven experience in building production-grade AI solutions.</li><li>Exceptional communication skills (must be able to explain complex ideas with clarity).</li><li>A results-driven mindset, must be a closer who takes ownership and delivers.</li></ul>Nice to Have<ul><li>Experience with LLMs, Generative AI, and model fine-tuning.</li><li>Experience in API integrations and microservices.</li><li>Exposure to data visualization tools and dashboards.</li></ul>Job Type: Full-timeWork Location: In person

AI/ML Engineer

Sharp Brains Ltd

Role SummaryWe are seeking a highly skilled and experienced AI, ML and DL Instructor to lead our hands-on vocational training program. The instructor will be responsible for teaching the practical application of Artificial Intelligence (AI) through core Machine Learning (ML) techniques and advanced Deep Learning (DL) architectures. The focus is on equipping students with job-ready skills to design, train, and deploy real-world AI solutions.Key ResponsibilitiesNAVTTC Course Development &amp; Delivery:<ul><li>Instruct on the architecture and application of modern LLMs (e.g., Transformer models like BERT, GPT, Llama, etc.) and related frameworks like Hugging Face.</li><li>Prompt Engineering: Teach best practices for constructing effective prompts, few-shot learning, and advanced retrieval techniques (like Retrieval-Augmented Generation - RAG) for specific use cases.</li><li>Model Specialization: Provide hands-on training in techniques for customizing LLMs, including Fine-Tuning and Parameter-Efficient Fine-Tuning (PEFT) on domain-specific datasets.</li><li>Deployment &amp; MLOps: Guide students through the entire LLM lifecycle, from data preparation (tokenization, embeddings) to deployment and integration into web applications using frameworks like Flask/Streamlit.</li><li>Ethical AI: Cover critical topics on LLM ethics, including addressing bias, mitigating hallucination, and ensuring model safety and responsible usage.</li></ul>A. Deep Learning (DL) &amp; NLP Fundamentals<ul><li>Transformer Architecture: Deep conceptual understanding of Attention Mechanisms, Self-Attention, and the difference between Encoder-only, Decoder-only, and Encoder-Decoder architectures.</li><li>Core NLP: Proficiency in Tokenization (subword tokenization), Embeddings, and common NLP tasks (Classification, Summarization, Text Generation).</li><li>Frameworks: Expertise in PyTorch and/or TensorFlow and primary use of the Hugging Face ecosystem.</li></ul>B. Large Language Model (LLM) Specifics<ul><li>Prompt Engineering: Mastery of zero-shot, one-shot, and few-shot prompting, as well as techniques like Chain-of-Thought (CoT) prompting.</li><li>Fine-Tuning: Practical experience with supervised fine-tuning, Low-Rank Adaptation (LoRA), and understanding the training phases (Pre-training vs. Fine-tuning).</li><li>Deployment &amp; Scaling: Experience with deploying LLMs, managing hardware constraints (e.g., using quantization/GPGPU), and integrating models into production systems.</li></ul>C. Artificial Intelligence (AI) Context<ul><li>RAG Implementation: Ability to design and implement Retrieval-Augmented Generation (RAG) pipelines to ground LLM responses in external, real-time data.</li><li>Data Curation: Skills in curating, cleaning, and preparing massive, high-quality text datasets for training and fine-tuning.</li><li>Ethical AI: Knowledge of model safety, fairness, and bias mitigation strategies specific to large-scale generative models.</li></ul>Qualifications and ExperienceBachelor&rsquo;s degree in Computer Science, Data Science, or a closely related field. Master's degree with a specialization in NLP or AI is highly preferred.Minimum 1 year of formal teaching, corporate training, or vocational instruction experience, demonstrating the ability to convey complex LLM concepts clearly.Certification Plus in NLP, Deep Learning, or Cloud ML platforms (e.g., Google Cloud/AWS/Azure AI certification).Job Types: Full-time, Contract Contract length: 12 monthsPay: Rs62,000.00 - Rs80,000.00 per monthWork Location: In person

Instructor of AI, ML and DL

Explore 323+ Nlp engineer in Lahore this December. Find roles across top companies and apply now to boost your career.

323 nlp engineer jobs IN Lahore

AI Engineer / API Integrator

AI Conversation Designer

AI Conversation Designer

AI Engineer

Sr. Python Developer

AI/ML Engineer

Instructor of AI, ML and DL