About the RoleWe are looking for an AI/ML Backend Engineer to join our technical team and help build the foundation of an AI-powered product from the ground up.This is a hands-on role for someone who can work across AI model fine-tuning, backend development, data pipelines, APIs, and MLOps. You will be responsible for helping turn early AI experiments into a reliable, scalable product ready for production.A key part of this role is working with Unsloth for efficient model fine-tuning and optimization. We are looking for someone who understands how to fine-tune models practically, improve performance, and prepare AI systems for real product use.You will work closely with the Product Manager and the data team during the first development phase, then help move the product toward launch and long-term growth.What You Will DoPrepare, clean, and structure datasets for AI model training and evaluation.Fine-tune AI models using Unsloth as a core tool.Work with modern fine-tuning techniques such as LoRA, QLoRA, PEFT, supervised fine-tuning, and dataset formatting.Build and improve ML pipelines for training, testing, deployment, and monitoring.Develop backend services using Python and FastAPI.Design and manage databases needed for the core product.Build secure, well-documented, and scalable APIs to connect AI models with future web and mobile applications.Deploy and maintain AI models in a production-oriented environment.Apply practical MLOps practices such as experiment tracking, model versioning, deployment, monitoring, and performance evaluation.Work closely with the Product Manager to turn business requirements into technical solutions.Participate in daily standups, sprint planning, and product discussions.Take ownership of technical decisions during the early stage of the product. Required Skills & RequirementsExperience Requirement1–4 years of experience in AI/ML engineering, backend development, or related technical roles.AI & Machine LearningStrong practical knowledge of Unsloth for efficient AI model fine-tuning.Experience with model fine-tuning, dataset preparation, training workflows, and evaluation.Understanding of LoRA, QLoRA, PEFT, tokenization, prompt formatting, and model optimization.Familiarity with tools such as Hugging Face Transformers, PyTorch, Pandas, NumPy, or similar.Ability to test, compare, and improve model outputs based on real product requirements.Backend DevelopmentStrong experience with Python.Practical backend development experience using FastAPI or a similar Python backend framework.Good understanding of database design and API architecture.Ability to build secure, scalable, and well-documented APIs.Ability to write clean, structured, and maintainable code.MLOps & DeploymentFamiliarity with MLOps concepts such as model deployment, monitoring, experiment tracking, and model versioning.Understanding of production AI workflows.Experience with Docker, cloud deployment, CI/CD, or model-serving tools is a plus.Workflow & Team SkillsGood understanding of Agile/Scrum workflows.Commitment to daily standups and sprint-based execution.Comfortable using AI-assisted coding tools such as Cursor, Claude Code, GitHub Copilot, or similar tools.Strong teamwork mindset and ability to collaborate with product, data, and engineering.Nice to HaveExperience with LLMs, RAG systems, AI agents, NLP, OCR, or computer vision.Experience with tools such as MLflow, DVC, Weights & Biases, Airflow, or similar.Experience building AI products in a startup or fast-moving product environment.Previous work on real AI projects, personal projects, freelance work, or shipped products.