AI Engineer / Software Developer

About YNOS

What You'll Work On

• Design and develop AI/ML-powered features for YNOS products.
• Build and maintain scalable Python backend services and APIs.
• Develop data pipelines for processing, enrichment, classification and analysis of startup and business data.
• Experiment with and productionise machine learning models for ranking, recommendation, classification, prediction and similarity problems.
• Work with LLMs and AI APIs where they provide meaningful value, including structured extraction, summarisation, classification and intelligent research workflows.
• Build evaluation frameworks and pipelines to measure model quality, accuracy and performance.
• Work with both structured and unstructured data and develop approaches to turn raw data into useful intelligence.
• Integrate AI/ML models into production applications rather than keeping them limited to notebooks or prototypes.
• Improve existing systems for performance, reliability, scalability and maintainability.
• Collaborate with product and engineering teams to translate ambiguous business problems into practical technical solutions.
• Contribute to architecture, technical decisions, testing, documentation and engineering processes.

What We're Looking For

• Strong programming skills in Python.
• Good understanding of software engineering fundamentals, including data structures and algorithms, OOPs, REST APIs, databases, Git, version control, debugging.
• Experience building backend applications or services using Python.
• Working knowledge of machine learning fundamentals and the ability to understand, implement and evaluate ML models.
• Familiarity with data processing using tools such as Pandas, NumPy or similar.
• Ability to work with databases such as MongoDB, PostgreSQL or other relational/NoSQL databases.
• Understanding of how to take a solution from prototype to production.
• Strong problem-solving ability and willingness to learn unfamiliar technologies independently.

Good to Have

• Experience with FastAPI, Flask or Django.
• Experience with scikit-learn, XGBoost, PyTorch or TensorFlow.
• Experience working with LLMs, embeddings, vector databases or RAG systems.
• Experience with AI APIs such as OpenAI, Anthropic, Gemini or similar.
• Familiarity with Docker, Redis, background jobs or workflow orchestration.
• Experience building data pipelines or working with large datasets.
• Understanding of model evaluation, experimentation and A/B testing.
• Familiarity with cloud infrastructure and deployment.
• Exposure to frontend technologies such as React / NextJS is a plus.

What We Value

How to Apply

• Please share your resume and relevant project / GitHub / portfolio links while applying.
• We are particularly interested in seeing things you have actually built, deployed or experimented with.