About the Role We are seeking a AI/ML Engineer to design, develop, and deploy cutting-edge machine learning solutions. You’ll work on end-to-end AI projects from research and experimentation to production deployment. This role is perfect for engineers who are passionate about building intelligent systems and have hands-on experience with the full ML lifecycle. Tech Stack ML/AI Frameworks: TensorFlow, PyTorch, scikit-learn, Hugging Face Programming: Python, R (optional) Data Science: pandas, numpy, matplotlib, seaborn, Jupyter MLOps: MLflow, Kubeflow, Docker, Kubernetes Cloud Platforms: AWS (SageMaker, Lambda, S3), Azure ML, GCP AI Platform Databases: PostgreSQL, MongoDB, Vector DBs (Pinecone, OpenSearch) What You’ll Do * Design and develop ML models from conception to production deployment * Integrate different AI systems and models into enterprise applications and SaaS * Conduct experiments and research to solve complex business problems with AI * Build data pipelines for model training and inference * Implement feature engineering and data preprocessing workflows * Fine-tune and optimize models for performance and accuracy * Deploy ML models using cloud services and containerization * Monitor model performance and implement retraining pipelines * Collaborate with data scientists to translate research into production systems
✅ Requirements Must Have: * 4+ years experience in machine learning engineering * Strong expertise in TensorFlow/PyTorch or similar technologies * Deep understanding of ML algorithms (supervised, unsupervised, deep learning) * Production ML experience — model deployment, monitoring, versioning * Python proficiency with data science stack (pandas, numpy, matplotlib) * Feature engineering and data preprocessing expertise * Cloud ML services experience (AWS SageMaker, Azure ML, or GCP AI Platform) * Statistics and mathematics fundamentals for ML * Upper-Intermediate English or higher
Nice to Have: * Research background — published papers, kaggle competitions * LLM fine-tuning experience (GPT, BERT, T5) * Reinforcement Learning knowledge * Edge deployment experience (TensorFlow Lite, ONNX) * Multi-modal AI systems experience
Team & Culture * Research-oriented environment with innovation focus * Cross-functional collaboration with data scientists and engineers * Remote-first with flexible working hours * Continuous learning culture with conference/course budgets * Open source contributions encouraged
What We Offer 100% Remote work with flexible schedule Cutting-edge AI projects with real-world impact Research time for exploring new ML techniques Long-term projects with technical growth opportunities Access to premium tools and cloud resources
