lead full stack engineer (.net, vue/react) - full remote Jobs in Islamabad

lead full stack engineer (.net, vue/react) - full remote

trainee software developer Jobs in Islamabad

trainee software developer

(remote) senior full-stack web developer Jobs in Islamabad

(remote) senior full-stack web developer

accounting & finance associate - remote (full time) Jobs in Islamabad

accounting & finance associate - remote (full time)

ai agent developer

ai research engineer pre training 100 remote

Tether Operations Limited

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job:
As a member of the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field.
You will have a deep expertise in LLM architectures, a strong grasp of pre-training optimization with a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: data curation, strengthening baselines, identifying and resolving existing pre-training bottlenecks to push the limits of AI performance.
Responsibilities:<ul><li>
Conduct pre-training AI models on large, distributed servers equipped with thousands of NVIDIA GPUs.</li><li>
Design, prototype, and scale innovative architectures to enhance model intelligence.</li><li>
Independently and collaboratively execute experiments, analyze results, and refine methodologies for optimal performance.</li><li>
Investigate, debug, and improve both model efficiency and computational performance.</li><li>
Contribute to the advancement of training systems to ensure seamless scalability and efficiency on target platforms.</li></ul><ul><li>
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&amp;D (with good publications in A* conferences).</li><li>
Hands-on experience contributing to large-scale LLM training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance.</li><li>
Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools.</li><li>
Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability.</li><li>
Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment.</li></ul></div>

AI Research Engineer - Pre training (100% Remote)

PointofIT

<ul><li>Note: </li></ul>Candidates whose primary experience is limited to integrating third-party LLMs, prompt engineering, or API-based AI solutions will not be considered.Job SummaryWe are looking for a core AI expert who designs, builds, trains, and optimizes machine learning and deep learning models from scratch. This role is not for candidates whose primary experience is integrating third-party LLMs, writing prompts, or consuming AI APIs.The ideal candidate has strong fundamentals in mathematics, statistics, and algorithms, and hands-on experience developing custom ML/DL models in Python for real-world production systems.What This Role IS<ul><li>Building custom ML/DL models</li><li>Designing model architectures</li><li>Training, tuning, and evaluating models</li><li>Working with raw data &rarr; features &rarr; models &rarr; deployment</li><li>Research-driven and engineering-driven AI work</li></ul>What This Role IS NOT❌ Prompt engineering❌ LLM API integration (OpenAI, Gemini, Claude, etc.)❌ &ldquo;Glue code&rdquo; around pre-trained models❌ No-code / low-code AI toolsKey Responsibilities<ul><li>Design and implement machine learning models from scratch (supervised, unsupervised, and deep learning)</li><li>Develop and train models using PyTorch / TensorFlow / JAX</li><li>Perform feature engineering, data preprocessing, and dataset curation</li><li>Optimize models for accuracy, performance, and scalability</li><li>Implement training pipelines, evaluation metrics, and validation strategies</li><li>Conduct experiments and research to improve model performance</li><li>Work with large datasets and handle model overfitting, bias, and drift</li><li>Deploy models into production and monitor real-world performance</li><li>Collaborate with backend and data engineers on model integration</li></ul>Required Skills (Must-Have)<ul><li>Strong Python (NumPy, Pandas, SciPy)</li><li>Deep understanding of ML fundamentals:</li><li>Linear algebra</li><li>Probability &amp; statistics</li><li>Optimization techniques</li><li>Hands-on experience building models using:</li><li>PyTorch or TensorFlow</li><li>Experience with:</li><li>Regression, classification, clustering</li><li>CNNs, RNNs, Transformers (architecture-level understanding)</li><li>Experience training models on real datasets (not just tutorials)</li><li>Ability to explain why a model works, not just how to call it</li></ul>Nice to Have<ul><li>Experience building:</li><li>Recommendation systems</li><li>Computer vision models</li><li>Time-series forecasting models</li><li>Anomaly detection systems</li><li>Experience with:</li><li>Distributed training</li><li>Model compression / quantization</li><li>MLOps (MLflow, Kubeflow, custom pipelines)</li><li>Research background or published work is a plus</li></ul>Experience Level<ul><li>5+ years of hands-on experience in machine learning / AI modeling</li><li>Proven experience building and deploying custom models</li></ul>Job Type: Full-timePay: Rs300,000.00 - Rs500,000.00 per monthApplication Question(s):<ul><li>Have you designed and trained machine learning or deep learning models from scratch (not just fine-tuned pre-trained models)?</li><li>Is your experience more than 5 years in hands-on ML/AI model development?</li><li>Have you deployed custom-trained ML/DL models into production environments?</li><li>Have you worked directly with raw datasets, including feature engineering and preprocessing?</li><li>Do you have experience handling overfitting, bias, data drift, or model degradation in real systems?</li><li>Are you willing to work onsite from 12:00 PM to 9:00 PM at our Evacuee Trust Complex (F-5), Islamabad office? (Yes/No)</li><li>How soon can you join if selected? (Immediately / 1&ndash;2 weeks / 1 month / More than 1 month)</li></ul>Work Location: In person

Senior AI / Machine Learning Engineer (Core Modeling – Python)

SME Careers

<div>
 As an hourly paid, fully remote Go Engineer for AI Data Training, you will review AI-generated Go code and explanations or generate your own, evaluate the reasoning quality and step-by-step problem-solving, and provide expert feedback that helps models produce answers that are accurate, logical, and clearly explained. You will assess solutions for correctness, readability, and adherence to backend-style best practices; identify errors in concurrency, error handling, or conceptual understanding; fact-check information; write high-quality explanations and model solutions that demonstrate idiomatic Go; and rate and compare multiple AI responses based on correctness and reasoning quality.
 
 This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world&rsquo;s largest AI companies and foundation model labs, and your work will directly help improve the world&rsquo;s premier AI models while giving you the flexibility of impactful, detail-oriented remote contract work.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
 </li>
 <li>
 Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
 </li>
 <li>
 Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
 
 </li>
 </ul>
 
 Your Profile
 
 
 <ul>
 <li>
 1&ndash;2+ years of professional Go programming experience, ideally focused on backend services, APIs, or systems work.
 </li>
 <li>
 Strong understanding of Go idioms, including clear error handling, composition over inheritance, and simple, readable interfaces.
 </li>
 <li>
 Hands-on software engineering experience building and maintaining backend-style Go applications in production environments.
 </li>
 <li>
 Ability to evaluate correctness and readability in backend-oriented Go code, including concurrency patterns, error propagation, and API design.
 </li>
 <li>
 Significant experience using LLMs or AI coding assistants while programming, combined with a disciplined approach to validating their output.
 </li>
 <li>
 Excellent English writing skills, capable of producing precise, structured, and pedagogical technical explanations.
 </li>
 <li>
 Minimum Bachelor&rsquo;s degree in Computer Science or a closely related technical field.
 </li>
 <li>
 Previous experience with AI data training, code review at scale, or evaluation of AI-generated technical content is strongly preferred; Minimum C1 English proficiency and an extremely detail-oriented working style are required.
 </li>
 <li>
 Highly preferred: hands-on experience with Go frameworks and libraries such as Gin, gRPC, or Echo in real projects.
 </li>
 <li>
 Preferred: merged PRs in Go open-source projects, competitive programming experience, cloud-native development exposure, and familiarity with Go performance profiling tools and techniques.
 </li>
 </ul>
</div>

Go Engineer

Skylabs AI

<div><h3 class="jobSectionHeader">About Us</h3>
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.<h3 class="jobSectionHeader">
The Role</h3>
We are seeking an exceptional Senior Backend Engineer to lead the architecture and implementation of our entire cloud-native infrastructure. This is a foundational role responsible for building the scalable, resilient, and secure microservices platform that our AI agents and developer tools will run on.
You will be responsible for everything from our API gateways and database architecture to the Kubernetes-based remote execution sandboxes. You will design the asynchronous systems that manage long-running agentic tasks and build the high-throughput pipelines for LLM inference and telemetry. The ideal candidate is a &quot;10x&quot; backend expert who has built and scaled complex, AI-driven systems in production.
Requirements<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul>
<li>Microservice Architecture: Design, build, deploy, and maintain our platform as a set of resilient, scalable microservices (e.g., auth, payments, agent orchestration).</li>
<li>Agent Orchestration Backend: Build the critical systems that manage the lifecycle of long-running agentic tasks, including state management and asynchronous communication (Kafka, RabbitMQ, etc.).</li>
<li>Remote Sandboxing: Architect and implement the containerized execution environments (Docker, Kubernetes) where agents can safely build, test, and run code.</li>
<li>LLM Inference Infrastructure: Deploy, manage, and wrap high-throughput LLM inference servers (NVIDIA Triton, vLLM) to serve models to our agent systems.</li>
<li>API Design: Design, secure, and manage our core APIs (REST and gRPC), including our public-facing MCP/ACP and internal service-to-service communication.</li>
<li>Data &amp; Telemetry: Build the high-throughput data ingestion pipeline to process and store massive volumes of telemetry and training data from our IDE clients.</li>
<li>Identity &amp; Payments: Implement and manage our authentication (OAuth2/OIDC) and payment/subscription (Stripe) systems.</li>
<li>Infrastructure &amp; Observability: Own our Infrastructure as Code (Terraform) and build out comprehensive observability (Prometheus, Grafana, Jaeger) across the entire stack.</li>
</ul><h3 class="jobSectionHeader">Qualifications &amp; Skills</h3><h3 class="jobSectionHeader">
Core Profile: Sr. Backend Engineer</h3><ul>
<li>Expertise in Microservice Architectures: Proven ability to design, build, deploy, and maintain a complex system as a set of resilient, scalable, and independent microservices.</li>
<li>Advanced API Design &amp; Management: Mastery of designing clean, secure, and high-performance APIs (both REST and gRPC). Experience with API gateways, versioning, and documentation.</li>
<li>Database-agnostic Expertise: Deep practical experience with both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB, Redis) databases, including data modeling, query optimization, and scaling.</li>
<li>Scalable AI/LLM Infrastructure: Must have experience building and scaling backend systems specifically for LLM use cases, understanding the unique demands of stateful, long-running agentic tasks.</li>
<li>Comprehensive Observability: Experience building and managing full-stack observability (e.g., using Prometheus, Grafana, ELK/OpenSearch, and distributed tracing like Jaeger) to ensure system health and performance.</li>
<li>Authentication &amp; Authorization: Expertise in implementing robust identity systems, including sign-up, OAuth2/OIDC, JWTs, and fine-grained Role-Based Access Control (RBAC).</li>
<li>Payment Gateway Integration: Experience integrating and managing payment and subscription systems (e.g., Stripe), including metering and subscription logic.</li>
</ul><h3 class="jobSectionHeader">Specific Experience Required:</h3>
1. Agent Orchestration &amp; Remote Sandboxing<ul>
<li>
Agentic Mode Backend: This is critical. Experience designing systems that manage the lifecycle of complex, long-running &quot;agent&quot; tasks.</li>
<li>Containerized Execution: Deep experience with Docker and Kubernetes (K8s) for orchestrating the &quot;remote sandbox&quot; where agent-generated code is built, run, and tested securely. Familiarity with lightweight virtualization (e.g., Firecracker) is a major plus.</li>
<li>Asynchronous Task &amp; Message Queues: Expertise in using systems like Kafka, RabbitMQ, or gRPC streams to manage communication between microservices, the IDE plugin, and the AI agents, ensuring no data is lost.</li>
</ul>
2. LLM Model Hosting &amp; Inference<ul>
<li>
Model Hosting: Hands-on experience deploying and managing high-throughput LLM inference servers like NVIDIA Triton, TGI, or vLLM on GPU-enabled infrastructure.</li>
<li>Inference API Integration: Building the backend service that securely wraps these inference endpoints, handles request batching, and serves them to the agent orchestrator.</li>
</ul>
3. High-Throughput Data &amp; Cloud Infrastructure<ul>
<li>
Telemetry Ingestion: Designing and building a high-throughput data pipeline to receive, process, and store the massive volume of telemetry and training data sent from the IDE plugin.</li>
<li>Infrastructure as Code (IaC): Mastery of Terraform or CloudFormation to provision and manage the entire cloud infrastructure repeatedly and reliably.</li>
<li>API Security &amp; Management: Implementing rate limiting, request validation, and service-to-service authentication (e.g., mTLS) to protect the MCP/ACP and other public-facing endpoints.</li>
<li>CI/CD &amp; DevOps: A strong DevOps mindset and experience building automated CI/CD pipelines (e.g., GitLab CI, GitHub Actions) for a microservices environment.</li>
</ul><h3 class="jobSectionHeader">Who You Are</h3>
You are a builder at heart, driven by curiosity and a desire to solve hard problems. You don't wait for instructions; you identify opportunities and seize them. You are comfortable with ambiguity and thrive in a fast-paced, in-depth environment where you are encouraged to experiment and push boundaries. You are a clear communicator who can articulate complex technical concepts and work collaboratively to achieve ambitious goals.
Benefits<h3 class="jobSectionHeader">
What We Offer</h3><ul>
<li>Competitive salary in USD</li>
<li>Comprehensive health allowance</li>
<li>Relocation allowance (if you're moving to Islamabad)</li>
<li>Monthly team events and offsites</li>
<li>A beautiful, collaborative office space</li>
<li>Work alongside world-class AI researchers and engineers</li></ul></div>

Senior Backend Engineer

Teamficient

AI Developer / AI EngineerCompany: TeamFicientLocation: RemoteJob Type: Full-timeSalary Range: To Be DeterminedAbout the RoleTeamFicient is seeking an experienced AI Developer / AI Engineer to join our dynamic team. In this role, you will be at the forefront of designing, developing, and scaling cutting-edge AI-powered applications that drive innovation and deliver exceptional value to our clients. This is a remote opportunity for a skilled professional passionate about applied artificial intelligence with a proven track record of building production-grade AI systems.Key Responsibilities<ul><li>Build and scale robust AI-powered applications that solve complex business challenges</li><li>Design and implement solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other applied AI systems</li><li>Develop and maintain backend services that support AI platforms and ensure seamless integration with cloud infrastructure</li><li>Deploy and optimize AI solutions on cloud platforms, including AWS, Azure, and/or Google Cloud Platform (GCP)</li><li>Collaborate with cross-functional teams to understand requirements and translate them into scalable AI architectures</li><li>Implement containerization and orchestration strategies using Docker and Kubernetes (K8s)</li><li>Design and develop RESTful APIs to enable the integration of AI capabilities across various applications</li><li>Monitor, troubleshoot, and optimize AI models and systems for performance, scalability, and reliability</li><li>Stay current with emerging AI technologies, tools, and best practices to continuously improve our AI capabilities</li><li>Participate in code reviews, documentation, and knowledge sharing to maintain high engineering standards</li></ul>Required Qualifications<ul><li>5+ years of professional experience in AI engineering, machine learning, or software engineering with a focus on AI systems</li><li>Proven experience deploying and maintaining AI solutions in production environments</li><li>Strong proficiency in Python and experience with AI/ML frameworks and libraries</li><li>Hands-on experience working with Large Language Models (LLMs) and related technologies</li><li>Demonstrated expertise in cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)</li><li>Solid understanding of API design and development principles and best practices</li><li>Experience with containerization technologies, including Docker and orchestration tools like Kubernetes (K8s)</li><li>Strong problem-solving skills and ability to architect scalable, efficient AI solutions</li><li>Excellent communication skills and ability to work effectively in a remote, collaborative environment</li><li>Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience</li></ul>Preferred Qualifications<ul><li>Experience with Retrieval-Augmented Generation (RAG) architectures and vector databases</li><li>Familiarity with MLOps practices and tools for model deployment and monitoring</li><li>Knowledge of additional programming languages such as Go, Java, or JavaScript/TypeScript</li><li>Experience with CI/CD pipelines and infrastructure as code (Terraform, CloudFormation)</li><li>Contributions to open-source AI/ML projects or active participation in the AI community</li><li>Experience working in agile development environments</li><li>Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field</li></ul>What We Offer<ul><li>Fully remote work environment</li><li>Opportunity to work on cutting-edge AI technologies and innovative projects</li><li>Collaborative and supportive team culture</li><li>Professional development opportunities and continuous learning</li></ul>TeamFicient is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.Job Type: Full-timeApplication Question(s):<ul><li>What is your expected monthly salary for this position (in USD)?</li></ul>Please provide your ideal and lowest negotiable salary. For example, Ideal: $1,200 Lowest: $800Work Location: Remote

Remote AI Developer / AI Engineer

Datamatics Global Services Ltd

<div><h3 class="jobSectionHeader">Job Title: DevOps / MLOps Engineer</h3>
Experience: 7&ndash;9 Years 
Location: Remote<h4 class="jobSectionHeader"> 
Job Summary</h4>
We are seeking a skilled DevOps Engineer with hands-on MLOps experience to design, automate, and manage scalable infrastructure and CI/CD pipelines for cloud-native and machine learning workloads. The role requires strong expertise in automation, container orchestration, and continuous delivery, with a focus on reliability, performance, and scalability.<h4 class="jobSectionHeader"> 
Key Responsibilities</h4><ul><li>
Design, build, and maintain CI/CD pipelines using Jenkins and automation tools</li><li>
Implement and manage MLOps pipelines for model training, deployment, monitoring, and retraining</li><li>
Deploy, manage, and scale containerized applications using Kubernetes</li><li>
Automate infrastructure provisioning and configuration using IaC tools</li><li>
Manage cloud infrastructure and services on Google Cloud Platform (GCP)</li><li>
Ensure high availability, security, and performance of platforms and pipelines</li><li>
Collaborate with data scientists and engineers to productionize ML models</li><li>
Monitor systems, optimize costs, and troubleshoot production issues</li></ul><h4 class="jobSectionHeader"> 
Required Skills &amp; Experience</h4><ul><li>
Strong experience as a DevOps Engineer with exposure to MLOps practices</li><li>
Hands-on expertise with Kubernetes (deployment, scaling, networking)</li><li>
Strong experience with Jenkins for CI/CD automation</li><li>
Experience with automation and scripting tools (Terraform, Ansible, Bash, Python, etc.)</li><li>
Strong understanding of containerization (Docker) and microservices architecture</li><li>
Experience with monitoring, logging, and alerting solutions</li></ul><h4 class="jobSectionHeader"> 
Nice to Have</h4><ul><li>
Experience with ML platforms such as Kubeflow, Vertex AI, or MLflow</li><li>
Knowledge of GitOps tools (ArgoCD, Flux)</li><li>
Experience with security, IAM, and compliance in cloud environments</li></ul>
YR6JMI01Y8</div>

DevOps / MLOps Engineer

<div><h2 class="jobSectionHeader">Job Title: Senior ML Engineer &ndash; MLOps &amp; Productionization</h2>
Level: Senior 
Employment Type: Full-time 
Experience: 7+ Years 
Location: Islamabad<h3 class="jobSectionHeader"> 
Role Overview</h3>
We are seeking a Senior ML Engineer to bridge the gap between experimental AI/ML prototypes and production-ready enterprise systems. As our AI/ML initiatives evolve from research to production, you will be responsible for operationalizing ML and LLM models, ensuring they run reliably at scale, and establishing robust engineering practices within our intelligence layer.
This role requires a hands-on engineer with deep Python expertise, strong MLOps experience, and the ability to deliver high-performance, containerized services that support large-scale, streaming data environments.<h3 class="jobSectionHeader">
Key Responsibilities</h3>
Production Transition &amp; Microservices Development<ul><li>
Refactor Python-based ML models and LLM chains from experimental notebooks into production-ready, containerized microservices</li><li>
Ensure robust versioning, logging, and monitoring of models in production</li><li>
Collaborate with AI/ML researchers to translate R&amp;D prototypes into scalable software</li></ul>
MLOps &amp; Deployment Pipelines<ul><li>
Build automated CI/CD pipelines for model deployment, monitoring, and retraining</li><li>
Implement model lifecycle management, including rollback strategies and reproducibility</li><li>
Integrate ML models into high-velocity streaming pipelines with low-latency requirements</li></ul>
Performance, Reliability &amp; Standards<ul><li>
Optimize ML inference logic for real-time and high-throughput environments</li><li>
Define and enforce coding standards, testing frameworks, and best practices for the AI/ML engineering team</li><li>
Ensure system stability, reliability, and observability across the intelligence layer</li></ul><h3 class="jobSectionHeader">
Technical Requirements</h3><ul><li>
Advanced Python Expertise: Beyond scripting &ndash; experience with FastAPI, design patterns, testing frameworks, and clean, maintainable code</li><li>
Containerization &amp; Orchestration: Deep experience with Docker; familiarity with Kubernetes or equivalent orchestration for ML workloads</li><li>
MLOps &amp; Deployment: Proven experience with CI/CD, model versioning, automated retraining, and tools such as MLflow, Kubeflow, or similar</li><li>
Experience operationalizing ML/LLM models in production, with strong focus on scalability and reliability</li></ul><h3 class="jobSectionHeader">
Nice to Have</h3><ul><li>
Experience with cloud-native AI/ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML)</li><li>
Familiarity with streaming data platforms (Kafka, Pulsar, or similar)</li><li>
Exposure to monitoring, logging, and alerting frameworks for ML systems</li><li>
Knowledge of enterprise-grade security and compliance practices for AI</li></ul><h3 class="jobSectionHeader">
Soft Skills</h3><ul><li>
Strong problem-solving and analytical thinking</li><li>
Ability to translate research prototypes into robust engineering solutions</li><li>
Excellent collaboration skills, capable of working across AI, data engineering, and DevOps teams</li><li>
High ownership mentality with a focus on production stability and scalability</li></ul><h3 class="jobSectionHeader">
Why Join</h3><ul><li>
Play a critical role in moving cutting-edge AI/ML into production</li><li>
Shape the MLOps strategy and best practices for a growing intelligence platform</li><li>
Work in a fast-moving, enterprise-scale AI/ML environment with real business impact</li></ul>
DWxqJxDANB</div>

Senior ML Engineer

Explore 462+ Ai research engineer pre training 100 remote in Islamabad this January. Find roles across top companies and apply now to boost your career.