Open position in multiple countries (India, Pakistan, Egypt). About the Role We’re looking for a Senior Backend Developer who can lead backend architecture, design RESTful APIs, and integrate intelligent systems into our mobile platform using Python , FastAPI , AWS , and ML-based recommendation engines . You’ll work closely with cross-functional teams including frontend, product, and data science — bringing new ideas to life while ensuring performance, scalability, and security. Key Responsibilities: Design and develop scalable backend services using Python and FastAPI . Build and maintain RESTful APIs for seamless communication between Flutter-based mobile apps and backend systems. Architect and manage cloud infrastructure on AWS , including ECS, EC2, Lambda, RDS, S3, CloudWatch, and CloudFront . Implement SQLAlchemy ORM and optimize PostgreSQL queries for high-performance database operations. Integrate machine learning models and recommendation systems (e.g., collaborative filtering, embeddings, NLP-based classification). Optimize cloud costs and implement budget tracking strategies across AWS and third-party platforms. Containerize and deploy services using Docker and orchestrate them in cloud environments. Collaborate with Agile teams to ship features quickly and efficiently. Ensure system reliability through monitoring, logging, and automated testing. Work on AI-driven content moderation , user behavior tracking , and personalization engines Mandatory Requirements: 5+ years of professional backend development experience. Strong proficiency in Python , especially with FastAPI . Deep knowledge of PostgreSQL , relational database design, and SQL optimization. Experience with SQLAlchemy ORM . Hands-on with AWS services : ECS, RDS, EC2, Lambda, S3, CloudWatch, CloudFront. Demonstrated ability in cost optimization and budget tracking on AWS or similar platforms. Experience with Docker and container orchestration (Kubernetes, ECS, etc.). Solid understanding of RESTful API design and JWT-based authentication . Excellent problem-solving skills and ability to work both independently and collaboratively. Experience working with Flutter or mobile app backend integration . Exposure to machine learning or recommendation systems (collaborative filtering, embeddings). Familiarity with NLP techniques for content classification/filtering. Experience with AI coding assistants like GitHub Copilot, Amazon CodeWhisperer, or ChatGPT. Knowledge of DevOps tools such as Terraform, Jenkins, or GitHub Actions. Strong technical writing and documentation skills. Experience in Agile/Scrum environments. Understanding of real-time data pipelines , event streaming (Kafka), or batch processing (Spark). What’s Offered? Full-time remote position. Build user-first products with global impact. Join a fast-moving, tech-driven team. Lead architecture decisions and mentor others. Competitive compensation and performance-based incentives. Opportunity to work on cutting-edge software projects in a collaborative environment. Supportive and innovative team culture with room for career advancement.

Location: Remote Employment Type: Full-time About the Role We are looking for a Senior Machine Learning Engineer to lead the development and deployment of AI/ML models for our platforms. In this role, you will drive technical strategy and you will be responsible for designing and deploying intelligent systems ,mentor junior engineers, and collaborate with cross-functional teams to deliver scalable, production-grade ML solutions. Key Responsibilities Independently design, build, and deploy machine learning models for core use cases. Drive the end-to-end lifecycle of ML projects—from scoping and architecture to implementation, deployment, and performance tuning. Maintain a hands-on approach in all aspects of development—from data preprocessing and feature engineering to model training, evaluation, and optimization. Lead technical reviews, provide constructive feedback, and help grow the team’s skill sets through coaching and knowledge sharing. Provide technical leadership and mentorship to junior engineers and data scientists, fostering a collaborative and high-performing team culture. Drive ML initiatives from ideation through production, ensuring scalability, performance, and maintainability. Collaborate with cross-functional teams including product, engineering, and operations to integrate intelligent solutions into user-facing products. Establish and promote ML best practices, including reproducibility, version control, testing,MLOps, and data governance. Oversee and guide the creation of scalable and maintainable ML pipelines and infrastructures. Stay ahead of industry trends and guide the adoption of new tools and techniques where relevant. Evaluate and integrate cutting-edge tools, frameworks, and techniques in NLP, deep learning, and computer vision. Own the quality, fairness, and compliance of ML systems, especially in sensitive use cases like content filtering and moderation. Design and implement machine learning models for automated content moderation , including toxicity, hate speech, spam, and NSFW detection. Build and optimize personalized recommendation systems using collaborative filtering, content-based, and hybrid approaches. Develop and maintain embedding-based similarity search for recommending relevant content based on user behavior and content metadata. Fine-tune and apply LLMs for moderation and summarization , leveraging prompt engineering or adapter-based methods. Deploy real-time inference pipelines for immediate content filtering and user-personalized suggestions. Ensure content moderation models are explainable , auditable , and bias-mitigated to align with ethical AI practices. Hands-on experience in content recommendation systems (e.g., collaborative filtering, ranking models, embeddings). Experience with content moderation frameworks , such as Perspective API, OpenAI moderation endpoints, or custom NLP classifiers. Strong knowledge of transformer-based models for NLP , including experience with Hugging Face, BERT, RoBERTa, etc. Practical experience with LLMs (GPT, Claude, Mistral) and tools for LLM fine-tuning or prompt engineering for moderation tasks. Familiarity with vector databases (e.g., FAISS, Pinecone) for similarity search in recommendation systems. Deep understanding of model fairness, debiasing techniques , and AI safety in content moderation . Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. 5+ years of hands-on experience in machine learning, NLP, or deep learning, with a track record of leading projects. Expertise in Python and machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, etc. Strong background in recommendation systems, content moderation, or ranking algorithms. Experience with cloud platforms (AWS/GCP/Azure), distributed computing (Spark), and MLOps tools. Proven ability to lead complex ML projects and teams, delivering business value through intelligent systems. Excellent communication skills, with the ability to explain complex ML concepts to stakeholders. Experience with LLMs (GPT, Claude, Mistral) and fine-tuning for domain-specific tasks. Knowledge of reinforcement learning, graph ML, or multimodal systems. Previous experience building AI systems for content moderation, personalization, or recommendation in a high-scale platform. Strong awareness of ethical AI principles, fairness, bias mitigation, and responsible data usage. Contributions to open-source ML projects or published research.