AI Software Engineer

Sunhat GmbH

Berufsfeld
Technik

Jetzt bewerben

AI Software Engineer, Sunhat GmbH

We are looking for a curious AI software engineer. You'll work on cutting-edge projects involving natural language processing (NLP), text generation, text classification, and semantic similarity search. Responsibilities include evaluating and fine-tuning machine learning models, integrating them into our platform, and optimizing performance for scalability and efficiency. You'll work closely with software engineers and sustainability experts, leveraging your expertise to seamlessly integrate machine learning and AI powered capabilities into our software solution.

Activities

Drive generative AI and machine learning initiatives from ideation to deployment, ensuring solutions are robust, scalable, and seamlessly integrated into our platform.
Work on natural language processing and generative AI tasks, such as text generation, semantic similarity, and classification, leveraging advanced models, fine-tuning them for specific sustainability use cases.
Collaborate closely with software engineers to integrate GenAI and traditional ML models directly into our platform, focusing on efficiency, security, and performance at scale.
Utilize modern LLMOps practices and TDD to ensure reliable, maintainable pipelines, ensuring models can be rapidly iterated and deployed.
Partner with product management, sustainability experts, and the engineering team to translate business requirements into powerful AI-driven features that enhance our product's capabilities and usability.

Requirements

Proficient in GenAI and Machine Learning : Multiple years of hands-on experience in NLP and generative models (such as Gemini, Mistral, Llama or similar) in production, particularly for text-based tasks. Experience with Vertex AI is a plus.
Programming and Model Integration Skills : Expertise in TypeScript and experience integrating language models into production systems with a focus on reliability, scalability, and security. Expertise in Python is a plus.
LLMOps and CI/CD Experience : Knowledge of CI/CD practices, ideally with GitHub, to streamline and automate model development and deployment.
Data Security and Performance Optimization : Strong understanding of security, data privacy, and performance tuning specific to machine learning and GenAI in cloud environments.
GenAI and NLP Expertise : Proficiency in applying GenAI to enhance user experiences, with a good grasp of advanced text generation, summarization, and other generative tasks relevant to sustainability data processing.
Collaborative and Quality-Driven : Values collaboration, engages in pair programming, and prioritizes high-quality work through peer code reviews.
Initiative and Adaptability : Takes the lead on new projects, drives them to production, and continuously learns and improves based on outcomes.

Application Process

Discovery Call
Technical Interview
Live Coding Challenge

Jetzt bewerben