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associate software engineer

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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-timeExperience:<ul><li>AI Engineer: 3 years (Required)</li></ul>Language:<ul><li>English (Required)</li></ul>Work Location: In person

AI/ML Engineer

Hazen Technologies Inc.

<div>Company Overview:
Hazen Technologies is a leading technology and BPO company having offices in USA and Pakistan. Today we stand as a premier driver of innovation, offering transformative IT solutions, managed services (back-office support), and creative &amp; digital marketing services tailored for a range of industries. Our core focus is on providing seamless solutions that add real value for our customers.
Job Location: Gulberg Lahore Pakistan.
Job Conditions: Onsite, full time, 02:00 pm to 11:00 pm PKT
Report to: Chief Software Architect
Responsible for designing, developing, and implementing cutting-edge AI and machine learning solutions. Passionate and skilled to join our growing technology team. The ideal candidate will have hands-on experience building AI-powered solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and modern machine learning techniques.
Key Responsibilities: 
<ul><li>
Design and implement AI-powered applications using Large Language Models (LLMs).</li>
<li>Develop and maintain Retrieval-Augmented Generation (RAG) pipelines for document search, knowledge retrieval, and conversational AI.</li>
<li>Work with LLM APIs and integrate them into production-grade applications.</li>
<li>Build and manage embedding pipelines and vector search solutions.</li>
<li>Apply machine learning principles for model evaluation, optimization, and performance improvement.</li>
<li>Collaborate with backend and frontend teams to integrate AI features into products.</li>
<li>Monitor and improve AI system performance, scalability, and reliability.</li>
<li>Stay updated with the latest advancements in Generative AI, LLM frameworks, and machine learning technologies.</li></ul>
Key Requirements:<ul>
<li>BS/MS in Computer Science, Artificial Intelligence, Data Science, or a related field.</li>
<li>Strong programming skills in Python.</li>
<li>Hands-on experience working with LLMs and their APIs.</li>
<li>Experience building or working with RAG-based architectures.</li>
<li>Understanding of machine learning fundamentals and model evaluation techniques.</li>
<li>Experience with embeddings, vector databases, and semantic search.</li>
<li>Familiarity with frameworks such as LangChain, LlamaIndex, or similar LLM orchestration tools.</li></ul>
Preferred / Nice to Have<ul>
<li>Experience with Azure AI services and Azure OpenAI.</li>
<li>Familiarity with vector databases such as Qdrant, Pinecone, or Weaviate.</li>
<li>Experience deploying ML/AI solutions in cloud environments (Azure preferred).</li>
<li>Knowledge of MLOps, model monitoring, and scalable AI system design.</li>
<li>Experience working with REST APIs and backend integration.</li></ul>
At Hazen Technologies, we value diversity and inclusivity in the workplace. We are committed to providing equal employment opportunities to all individuals, regardless of race, gender, age, sexual orientation, religion, or disability.
Join our team and be a part of shaping the future of AI and machine learning at Hazen Technologies. Apply now! and make sure to fill out the form.</div>

Senior AI/ML Engineer

HR POD Careers

<div>
 
 
 Requirements:
 
 
 
 
 <ul>
 <li>
 Strong experience with FastAPI (or equivalent async frameworks), including dependency injection, UV, Pydantic, and async/await patterns (including thread pool executors for blocking operations).
 </li>
 <li>
 Solid understanding of REST API design, including multi-tenancy, pagination, filtering, JWT/OAuth2 authentication, and structured error handling.
 </li>
 <li>
 Proficiency in SQLAlchemy (including async sessions), raw parameterized queries, schema design, and migrations.
 </li>
 <li>
 Hands-on experience integrating multiple LLM providers (e.g., OpenAI, Anthropic, AWS Bedrock, Ollama, Google Gemini, Snowflake Cortex) using provider abstraction layers.
 </li>
 <li>
 Experience with JSON response validation, markdown/code-block extraction, and fallback error handling (preferably using frameworks like Pydantic).
 </li>
 <li>
 Knowledge of prompt engineering techniques, including context injection, temperature/token tuning, and confidence scoring.
 </li>
 <li>
 Familiarity with embedding-based retrieval and similarity scoring.
 </li>
 <li>
 Experience with production-grade agentic frameworks such as Pydantic AI (structured output generation, agents).
 </li>
 <li>
 Strong experience with gradient boosting models (e.g., XGBoost, LightGBM), including GPU-accelerated training, hyperparameter tuning, and evaluation.
 </li>
 <li>
 Expertise in segmentation, anomaly detection, and feature engineering on high-frequency sensor data.
 </li>
 <li>
 Experience with train/test splits, feature engineering, model evaluation (R&sup2;, MAE, etc.), and experiment tracking (e.g., MLflow).
 </li>
 <li>
 Understanding of when to combine classical ML with LLM-based components (e.g., LLM-assisted labeling, embedding features in tree models).
 </li>
 <li>
 Strong database knowledge, including complex schemas, JSONB, partitioned tables, row-level security, query optimization, and vector extensions (e.g., pgvector).
 </li>
 <li>
 Familiarity with NoSQL databases like MongoDB and specialized databases such as Redis and Qdrant is a plus.
 </li>
 <li>
 Experience with Snowflake (including Snowpark, Model Registry, and Cortex) or equivalent platforms.
 </li>
 <li>
 Hands-on experience with AWS services such as Bedrock, ECS, and EC2.
 </li>
 <li>
 Experience with Docker and CI/CD pipelines.
 </li>
 <li>
 Familiarity with S3 or equivalent object storage solutions.
 </li>
 <li>
 Ability to work within VPN-gated infrastructure.
 </li>
 <li>
 Experience across multiple client environments or industries (consulting background preferred).
 </li>
 <li>
 Exposure to Industrial IoT or sensor data (high-frequency telemetry, signal processing).
 </li>
 <li>
 Experience in NL-to-SQL or text-to-query system design.
 </li>
 <li>
 Ability to handle multilingual data and implement internationalization.
 
 
 
 </li>
 </ul>
 
 
 Responsibilities:
 
 
 
 
 <ul>
 <li>
 Design and integrate LLM-powered features, including conversational interfaces, AI agents, structured generation, and retrieval-augmented systems.
 </li>
 <li>
 Build and maintain ML pipelines for prediction, anomaly detection, classification, and time-series analysis.
 </li>
 <li>
 Develop backend APIs and services connecting data sources, models, and client-facing applications.
 </li>
 <li>
 Work with structured and unstructured data across relational databases, data warehouses, and external APIs.
 </li>
 <li>
 Optimize model performance and scalability for production environments, including monitoring and fine-tuning.
 </li>
 <li>
 Collaborate with cross-functional teams (product, data, and engineering) to translate business requirements into technical solutions.
 </li>
 <li>
 Ensure code quality, documentation, and best practices for deployment, testing, and maintainability.
 
 </li>
 </ul>
</div>

Senior AI/ML Engineer (Remote, EST, Anywhere in Pakistan, CAD Salary)

92Techno

We are seeking an experienced AI/GenAI Solution Architect to lead the design and delivery of enterprise-grade AI solutions.Responsibilities<ul><li>Engage with clients early to understand AI/GenAI/ML use cases and business requirements</li><li>Design proposed AI architectures and delivery approaches for opportunities</li><li>Provide effort estimates, assumptions, and implementation roadmaps for AI components</li><li>Lead end-to-end AI/GenAI solution architectures including data, models, integration, and deployment</li><li>Own scoped AI work packages delivered by the AI CoE within larger delivery projects</li><li>Ensure AI solutions are production-grade, secure, scalable, and maintainable</li><li>Collaborate with delivery teams for integration, handover, and deployment support</li><li>Establish reusable reference architectures, patterns, and best practices</li><li>Lead AI-enabled development initiatives across delivery teams</li><li>Standardize AI tools and workflows across the software development lifecycle (requirements, design, coding, testing, documentation)</li><li>Maintain awareness of emerging AI tools, models, and industry trends</li><li>Support internal incubation efforts and AI technology radar initiatives</li><li>Guide and mentor junior AI engineer and data analysts, providing technical direction, support, and feedback to elevate team expertise.</li></ul>Required Qualifications<ul><li>8+ years of experience in solution architecture, AI/ML engineering, or related roles</li><li>Strong understanding of AI/ML concepts, GenAI architectures, and modern model ecosystems</li><li>Experience designing AI solutions for enterprise clients, including integration into business applications</li><li>Hands-on familiarity with GenAI patterns such as RAG, agents, embeddings, and prompt engineering</li><li>Strong communication and stakeholder management skills, especially in client-facing settings</li><li>Ability to work across pre-sales, delivery, and engineering teams</li></ul>Preferred Skills<ul><li>Experience with cloud AI platforms (Azure AI, AWS SageMaker, GCP Vertex AI)</li><li>Familiarity with MLOps practices, evaluation frameworks, and deployment pipelines</li><li>Exposure to enterprise security, compliance, and responsible AI governance</li><li>Prior experience in consulting or client delivery environments</li></ul>Job Type: Full-timePay: Rs500,000.00 - Rs600,000.00 per monthWork Location: In person

AI Solution Architect

Skylinx Technologies

AI Engineer &ndash; Lahore (On-Site)We are hiring an in-house AI Engineer to join our Lahore-based engineering team. This role focuses on building and deploying AI-driven features for our custom platform, including data intelligence, competitive alerts, and user-facing AI interfaces. You will work closely with backend and product teams and have direct ownership of AI integrations and deployments.Key Responsibilities<ul><li>Work with existing machine learning models and large language models (LLMs).</li><li>Deploy and manage AI/ML models on private cloud or self-hosted infrastructure.</li><li>Integrate third-party AI tools and APIs (e.g., Groq, OpenAI, Hugging Face, vector databases).</li><li>Build data pipelines by connecting AI models with relational and NoSQL databases.</li><li>Design and implement competitive alerts, insights, and notifications from structured and unstructured data.</li><li>Develop APIs and basic interfaces to expose AI capabilities within the platform.</li><li>Optimize inference performance, cost, and scalability.</li><li>Ensure data security and privacy in AI workflows.</li><li>Collaborate closely with in-house backend, frontend, and product teams.</li></ul>Required Skills &amp; Qualifications<ul><li>2+ years of professional experience in AI/ML engineering or applied AI development.</li><li>Strong proficiency in Python.</li><li>Hands-on experience with machine learning models, LLMs, or inference pipelines.</li><li>Experience deploying models on private cloud, VPS, or on-prem infrastructure.</li><li>Familiarity with third-party AI platforms and tools (e.g., Groq, OpenAI, Anthropic).</li><li>Experience working with databases (MySQL, PostgreSQL, MongoDB, etc.).</li><li>Ability to build and consume REST APIs.</li><li>Basic experience with interfaces or dashboards for AI-powered features.</li><li>Strong problem-solving skills and ability to work in an on-site team environment.</li></ul>Nice to Have<ul><li>Experience with RAG (Retrieval-Augmented Generation) systems.</li><li>Knowledge of alerting systems, recommendation engines, or analytics dashboards.</li><li>Familiarity with Docker, Kubernetes, or MLOps workflows.</li><li>Experience in SaaS or data-driven platforms.</li><li>Frontend exposure (React, Vue, or similar).</li></ul>What We Offer<ul><li>On-site role in Lahore with a collaborative engineering team.</li><li>Opportunity to build production-grade AI systems.</li><li>Competitive salary</li><li>Long-term growth and learning opportunities.</li><li>Direct impact on core product features.</li></ul>How to ApplyPlease share:<ul><li>Your updated resume</li><li>GitHub or project links (if available)</li><li>Short summary of AI or ML projects you&rsquo;ve worked on</li></ul>Work Location: In person

AI Engineer (In-House)

CodeNinja

<div>About CodeNinja
CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
Role Purpose
Lead the ERP program&rsquo;s data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
Key Responsibilities<ul><li>Conduct comprehensive assessment of legacy data sources:</li></ul>
o Inventory, Maintenance (MRO), Procurement, HR, Technical Docs<ul><li>Identify:</li></ul>
o Data quality issues (duplicates, missing, inconsistencies)
o Data ownership and governance gaps
o Redundant/siloed datasets<ul><li>Define data cleansing and standardization approach</li><li>Produce Data Readiness Assessment Report</li><li>Define end-to-end Data Migration Strategy, including:</li></ul>
o Migration approach (phased, module-wise, or big-bang)
o Data prioritization (master data vs transactional vs historical)<ul><li>Develop Data Mapping Specifications:</li></ul>
o Legacy ERP field-level mappings
o Transformation rules and standardization logic
o Handling of missing/invalid data<ul><li>Define Data Cleansing &amp; Preparation Plan:</li></ul>
o Deduplication rules
o Data enrichment where required
o Validation checkpoints before migration<ul><li>Design Migration Execution Plan:</li></ul>
o Migration cycles (mock runs, dry runs, final cutover)
o Rollback strategy in case of failure
o Downtime and cutover planning<ul><li>Define Data Validation &amp; Reconciliation Framework:</li></ul>
o Pre-migration vs post-migration validation rules
o Reconciliation reports (counts, totals, relationships)
o Sign-off criteria for each module<ul><li>Produce key deliverables:</li></ul>
o Data Migration Plan
o Data Mapping Documents
o Data Validation &amp; Reconciliation Reports<ul><li>Identify and enable AI/ML use cases, such as:</li></ul>
o Predictive maintenance modeling
o Inventory demand forecasting
o Supplier performance analytics<ul><li>Leverage AI tools for:</li></ul>
o Data profiling and anomaly detection
o Data quality assessment and cleansing recommendations
o Advanced analytics and insights generation<ul><li>Define enterprise conceptual data model:</li></ul>
o Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs<ul><li>Establish:</li></ul>
o Entity relationships
o Master data definitions
o Data standardization rules<ul><li>Support BI teams for dashboards and analytics</li><li>Align data models with business workflows</li><li>Ensure requirements are data-feasible and consistent</li></ul> 
Requirements 
3. Required Skills &amp; Experience
Mandatory<ul><li> 5 - 8 years in Data Analyst / Data Architecture roles</li><li>Experience in large-scale ERP or enterprise data transformation programs</li><li>Strong expertise in:</li></ul>
o Data modelling (conceptual &amp; logical)
o Data migration and cleansing
o Data warehousing and reporting
Technical Expertise<ul><li>Strong knowledge of:</li></ul>
o ETL processes and migration tools
o SQL and relational databases
o API-based integrations<ul><li>Experience with BI tools (Power BI, Tableau)</li></ul>
Preferred<ul><li>Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)</li><li>Exposure to:</li></ul>
o Maintenance (MRO) data
o Inventory systems
o Technical documentation repositories<ul><li>Demonstrated experience using AI/ML tools or platforms, such as:</li></ul>
o Data analysis and prediction tools
o AI-assisted data modeling or profiling tools<ul><li>Ability to translate data into AI-driven insights for decision-making</li></ul>
Why Join CodeNinja?<ul><li>
Work on impactful ERP transformation projects at enterprise scale
</li><li>Shape end-to-end data strategy, migration, and architecture
</li><li>Leverage AI/ML for advanced data insights and analytics
</li><li>Collaborate with cross-functional teams and drive business decisions
</li><li>Build scalable data models and governance frameworks
</li><li>Grow in a culture of innovation, ownership, and continuous learning</li></ul>
Equal Opportunity Statement
We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply. 
Benefits 
<ul><li>
Provident Fund</li><li>
Gym Membership
</li><li>Leaves as per the company policy
</li><li>Company-paid trips
</li><li>Easy Loan Facility for Employees
</li><li>Yearly increment
</li><li>Maternity Benefits (Leaves &amp; WFH)
</li><li>Health Insurance (Maternity covered) &ndash; includes spouse and parents (till age 80)</li></ul></div>

Data Engineer/Data Architect

My Digital People

AI Engineer &ndash; Generative, Agentic AI &amp; AutomationWe&rsquo;re looking for a hands-on AI Engineer (2&ndash;3 years experience) who can design, build, and scale AI-powered automations and agentic systems. This role focuses on practical implementation &mdash; from intelligent workflows and voice agents to deploying open-source models on cloud infrastructure.You&rsquo;ll work on end-to-end automation systems that streamline business processes using AI.Key ResponsibilitiesAI Automation &amp; Workflows (Core Focus)<ul><li>Design and build end-to-end AI automations for business processes</li><li>Create intelligent workflows using n8n, Make, Zapier, Flowise, and custom Python</li><li>Automate tasks such as lead handling, customer support, data processing, and reporting</li><li>Connect multiple systems (CRMs, databases, APIs) into seamless automated pipelines</li><li>Build event-driven and trigger-based automation systems</li></ul>Agentic AI Systems<ul><li>Develop agentic workflows using LangChain, LangGraph, or similar tools</li><li>Architect multi-agent systems with task delegation and decision-making</li><li>Enable agents to interact with tools, APIs, and real-world data</li></ul>AI Systems &amp; Integrations<ul><li>Build AI applications across chat, voice, image, and video</li><li>Integrate AI with external tools using APIs, MCP, and webhooks</li><li>Orchestrate multiple AI providers (OpenAI, Anthropic, Google, open-source)</li></ul>Voice AI<ul><li>Develop and deploy voice agents using Vapi, ElevenLabs, or similar platforms</li><li>Design real-time conversational experiences</li></ul>RAG &amp; Knowledge Systems<ul><li>Build and maintain knowledge bases and RAG pipelines</li><li>Handle document ingestion, chunking, and embedding workflows</li></ul>Deployment &amp; Infrastructure<ul><li>Deploy and manage open-source models on cloud platforms (AWS, Azure, GCP)</li><li>Work with Docker and basic Kubernetes</li><li>Ensure scalability, monitoring, and cost control</li></ul>Prompt Engineering &amp; System Design<ul><li>Design robust prompts and multi-turn AI systems</li><li>Optimize context handling and response accuracy</li></ul>Evaluation &amp; Optimization<ul><li>Build evaluation frameworks (LLM-as-judge, human review)</li><li>Implement logging and observability (LangSmith, Helicone, or similar tools)</li><li>Optimize performance and cost through caching and model routing</li></ul>Security &amp; Reliability<ul><li>Implement AI guardrails (prompt injection protection, PII handling)</li><li>Ensure safe, reliable, and production-ready deployments</li></ul>Required Skills &amp; Experience<ul><li>2&ndash;3 years of experience in AI/ML, automation engineering, or AI-driven development</li><li>Strong Python skills</li><li>Hands-on experience with automation tools (n8n, Make, Zapier, or similar)</li><li>Experience building AI automations or workflow systems</li><li>Familiarity with LangChain, LangGraph, or similar frameworks</li><li>Strong understanding of APIs, webhooks, and system integrations</li><li>Experience with cloud platforms (AWS, Azure, or GCP)</li><li>Knowledge of prompt engineering and AI system design</li><li>Understanding of AI system evaluation, logging, and debugging</li></ul>Nice to Have<ul><li>Experience with vector databases (Pinecone, FAISS, Weaviate, Qdrant)</li><li>Familiarity with AI development tools (Cursor, Claude Code)</li><li>Experience with voice/telephony or real-time systems</li><li>Exposure to fine-tuning techniques (LoRA, QLoRA)</li><li>Experience with business process automation (BPA) systems</li></ul>EducationBachelor&rsquo;s degree in Computer Science, Engineering, Data Science, or equivalent practical experience.Job Type: Full-timeWork Location: In person

Automation Engineer (n8n & Zapier)+Model Training

Explore 268+ Ai ml engineer in Lahore this April. Find roles across top companies and apply now to boost your career.