Design, build, and scale AI and GenAI features within Manatals recruitment platform
Lead the development of:
AI agents for candidate screening and communication
Semantic search and matching engines
Resume parsing in multiple languages
Generative tools for resume/job summarization, enrichment, and candidate sourcing
Natural language interfaces using LLMs (e.g., OpenAI, Claude, Mistral)
Own end-to-end ML and GenAI workflows: data preparation, model training/fine-tuning, evaluation, and production deployment
Continuously evaluate and optimize models for accuracy, latency, and cost
Collaborate with product and engineering teams to deliver robust, scalable, and user-friendly AI features
Stay up-to-date with the latest research, tools, and APIs in AI and GenAI and bring innovative ideas into the product
Help define best practices for safe, efficient, and reliable deployment of AI/GenAI systems in production
Requirements
Bachelors or Masters degree in Computer Science, Mathematics, Statistics, or a related quantitative field
Proven experience as a software engineer, with ownership of features deployed in production environments
Solid understanding of the full software development lifecycle, including CI/CD, monitoring, and observability in high-load systems
Strong programming skills in Python, with hands-on experience using libraries like NumPy, Pandas, Scikit-learn, Transformers, and TensorFlow or PyTorch
Experience working with LLMs (e.g., OpenAI, Claude, Mistral) and frameworks for GenAI development (LangChain, PromptLayer, etc.)
Solid grounding in machine learning algorithms supervised, unsupervised, and deep learning
Experience with experiment design, model evaluation, A/B testing, and metrics-driven development
Proficiency in SQL and working with large datasets (data cleaning, feature engineering, etc.)
Good knowledge of cloud infrastructure, especially AWS (e.g., S3, EC2, Lambda)
Familiarity with containerization and orchestration tools (e.g., Docker, ECS, Kubernetes)
Strong understanding of modern web application architectures and APIs
Excellent communication skills and ability to work cross-functionally
Experience in a B2B SaaS environment is a strong plus
Bonus: exposure to MLOps practices (model versioning, monitoring, retraining pipelines)
