Software Engineer I - AI and ML
Posted Apr 28, 2026
As a passionate Python and AI/ML Engineer with a minimum of 4 years of hands-on experience, you will thrive in fast-paced environments and love solving complex problems with data and algorithms. At Zinnia, you will have the opportunity to design, develop, and deploy machine learning models and Generative AI solutions to create real business impact. Here is what you will be responsible for:
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Designing, developing, and deploying machine learning models and Generative AI solutions, including classification, clustering, summarization, search & ranking, and information extraction. - Owning end-to-end ML pipelines, from data ingestion and preprocessing through model training, deployment, and production monitoring. - Collaborating with cross-functional teams to translate business requirements into AI-driven features, applying NLP, outlier detection, and deep learning techniques where applicable. - Building robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments. - Optimizing database interactions and ensuring efficient data storage and retrieval for AI applications across SQL and NoSQL systems. - Staying current with the latest advances in AI/ML, integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products. Qualifications required for this role include:
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Strong hands-on proficiency in Python for building, scripting, and deploying AI/ML systems. - Applied expertise across supervised, unsupervised, and deep learning, including classification, clustering, and outlier detection. - Hands-on experience with Generative AI, specifically building with LLMs, prompt engineering, RAG pipelines, summarization, and AI-powered features. - Proficiency in NLP & Search/ Ranking, utilizing processes like NER, embeddings, semantic search, and ranking models. - Experience in API development, designing and shipping secure, well-documented RESTful APIs exposing ML models as production-ready services. - Proficiency in databases, including SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads. Good to have skills include: