of Git/GitHub workflows and DevOps tooling Nice to have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based systems More ❯
or persona-based evaluations. Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen), Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products. Research experience (e.g., Master’s project, internship at More ❯
or persona-based evaluations. Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen), Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products. Research experience (e.g., Master’s project, internship at More ❯
containerized applications, particularly multi-container architecture.Experience with biological or scientific data (e.g., genomics, transcriptomics, proteomics) or pharmaceutical industry experience, especially in designing data visualisations.Knowledge of agent-based approaches (e.g., LangGraph, PydanticAI, AutoGen).If you're looking for a role where your skills will make a significant impact, apply now with your updated CV to become a part of our dynamic More ❯
GitHub). Preferred Qualifications Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen). Prior experience conducting user research for AI applications. Knowledge of AI/ML evaluation and benchmarking approaches, including safety and robustness evaluations. Web-based front end development More ❯
GitHub). Preferred Qualifications Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen). Prior experience conducting user research for AI applications. Knowledge of AI/ML evaluation and benchmarking approaches, including safety and robustness evaluations. Web-based front end development More ❯
agile development cycles and code reviews Key Skills: Python, React, TypeScript, Git/GitHub, cloud infrastructure (GCP), agile development, automated testing Nice to Have: Experience with AI safety evaluations, LangGraph, PydanticAI, or AutoGen frameworks Ideal for: Full stack engineers interested in building user-facing AI tools and safety-focused GenAI systems. More ❯
modern software development tools and practices (e.g., Git/GitHub). Experience deploying AI/ML-powered applications, especially those involving NLP, language models, or agent-based frameworks (e.g., LangGraph, PydanticAI, AutoGen). Background in user research specific to AI applications. Knowledge of AI/ML evaluation techniques, including safety and robustness assessments. Experience in web-based frontend development. If More ❯
You will work closely with HR stakeholders, data scientists, and legal compliance teams to build secure and scalable multi-agent AI solutions using modern frameworks such as LangChain, AutoGen, LangGraph, and RAG. Key Responsibilities: Architect and implement AI-powered tools to automate and enhance HR workflows (e.g., onboarding, employee queries, policy navigation). Design and deploy conversational agents using LangChain … and AutoGen for internal use. Build modular and scalable pipelines using LangGraph for multi-agent orchestration. Integrate RAG systems to enable context-aware document retrieval from internal HR/legal databases. Required Skills & Experience: Solid exposure in AI/ML engineering, with a strong focus on NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong More ❯
