AI/ML Full Stack Developer

We are looking for an experienced AI/ML Full Stack Developer to join our team onsite in Johar Town, Lahore. The ideal candidate will have a strong passion for building intelligent systems, scalable applications, and AI-powered products. This role requires managing the entire AI/ML product lifecycle—from research and development through deployment, optimization, and production monitoring—while also contributing to modern full stack web application development. Immediate joiners are preferred. The starting salary is PKR 350,000, with final compensation determined by experience, technical skills, and interview performance.

Key Responsibilities

Research, design, develop, and implement Machine Learning and Deep Learning models. Fine-tune, optimize, and deploy Large Language Models (LLMs) and Generative AI systems. Build and manage end-to-end AI/ML pipelines, including data collection, preprocessing, training, evaluation, deployment, and monitoring. Oversee the complete AI/ML lifecycle, including experimentation, testing, deployment, scaling, optimization, and maintenance.

Deploy AI/ML solutions into production environments with a focus on scalability, reliability, latency optimization, and performance. Monitor and improve model accuracy, inference speed, and infrastructure efficiency. Develop scalable frontend and backend applications for AI-powered platforms. Design and integrate REST APIs, microservices, and real-time data pipelines.

Collaborate closely with product, engineering, and design teams to deliver AI-driven solutions and features. Implement MLOps practices such as CI/CD pipelines, containerization, model serving, and automated deployments. Stay updated with emerging AI technologies, frameworks, and modern full stack development trends.

Required Qualifications

A minimum of 6 years of hands-on experience in AI/ML engineering and development with proven production-level expertise is required. Experience working directly with international clients through platforms like Upwork, staff augmentation, or enterprise engagements is highly advantageous. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and Keras is essential.

Candidates must demonstrate experience managing the full AI/ML lifecycle—from model development to deployment and production monitoring. Hands-on experience deploying AI/ML applications in cloud or production environments is necessary. A strong understanding of MLOps, CI/CD pipelines, model serving, and infrastructure optimization is expected.

Expertise in NLP, Computer Vision, Generative AI, LLMs, or Diffusion Models is required. Proficiency in frontend technologies such as React.js, Next.js, or Angular, along with backend frameworks like Node.js, Django, or FastAPI, is essential. Familiarity with databases including PostgreSQL, MongoDB, or MySQL is important.

Experience with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI is preferred. Hands-on knowledge of Docker, Kubernetes, and cloud platforms including AWS, GCP, or Azure is required. A strong foundation in software architecture, APIs, distributed systems, and scalable application design is critical. Solid mathematical skills in Linear Algebra, Calculus, Probability, and Statistics are also necessary. Excellent analytical, problem-solving, and communication skills are expected.

Preferred Qualifications and Benefits

Experience building AI-powered SaaS products or enterprise-grade AI applications is a plus. Familiarity with Vector Databases, Retrieval-Augmented Generation (RAG) pipelines, AI Agents, or Autonomous Systems will be advantageous. Knowledge of distributed AI infrastructure and scalable model serving is beneficial.

Experience integrating LLM APIs and building AI automation workflows is desirable. Familiarity with AI ecosystem tools such as LangChain, LlamaIndex, Pinecone, Weaviate, or ChromaDB is a strong asset. This is a full-time, onsite position with working hours from 2:00 PM to 11:00 PM, five days a week.

Candidates should be prepared to demonstrate their expertise across the complete AI/ML lifecycle, including hands-on work with frontend and backend technologies, cloud deployments, and MLOps practices. This opportunity is ideal for professionals eager to work in a dynamic environment focused on cutting-edge AI solutions.