pbThis position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML Engineer based in Italy. /b /ppJoin a mission-driven engineering team developing practical AI systems that address real-world challenges in healthcare, agriculture, education, and international development. As an AI/ML Engineer, you will design, build, evaluate, deploy, and continuously improve AI-powered applications used by nonprofit organizations and their communities. You will work on solutions ranging from clinical copilots and AI coaching tools to agricultural advisory chatbots and evaluation infrastructure. Collaborating with behavioral scientists, researchers, and embedded engineers, you will translate applied AI research into reliable, scalable products and reusable technical resources. You will also help partner organizations strengthen their own AI capabilities through mentorship, open-source contributions, and knowledge sharing. This fully remote role offers substantial technical ownership and the opportunity to apply advanced AI engineering to initiatives that can improve outcomes for millions of people. /ph3Accountabilities: /h3pIn this role, you will build and improve production-ready AI systems while helping nonprofit partners adopt effective, measurable, and responsible AI practices. Your work will combine hands-on engineering, applied research, experimentation, and collaboration with teams working directly in the field. /pulliDesign, build, evaluate, deploy, and improve machine learning systems and AI-powered applications for real-world use cases. /liliContribute to open-source AI evaluation infrastructure and tools that help nonprofit organizations assess and improve their AI products. /liliWork closely with behavioral scientists, researchers, and field teams to identify recurring challenges and translate findings into reusable tools, frameworks, playbooks, and technical publications. /liliDevelop rigorous evaluation methods for AI systems, including appropriate datasets, evaluation criteria, and measurable performance improvements. /liliBuild and iterate on production-grade LLM applications and agentic systems, improving their reliability, usefulness, and performance for intended users. /liliRelease meaningful technical innovations from partner projects as open-source contributions whenever appropriate. /liliDeliver solutions through rapid development and deployment cycles, using experimentation and measurable feedback to guide improvements. /liliDocument technical decisions, maintain engineering standards, and ensure AI components remain reliable and maintainable. /liliMonitor developments in applied AI research, assess relevant advances, and test promising approaches in practical settings. /liliAdvise and support nonprofit organizations developing generative AI products, helping them adopt effective engineering practices, tools, and workflows.



/liliMentor partner organization staff and help strengthen their internal technical capabilities and responsible AI practices. /liliContribute to workshops, seminars, and knowledge-sharing initiatives that communicate lessons and best practices from ongoing projects. /liliConduct site visits to understand operational challenges, observe how AI tools are used, and recommend technical improvements based on direct user needs. /liliTake initiative in identifying problems, defining solutions, and driving projects through implementation and deployment. /li /ulh3Requirements: /h3pThe ideal candidate combines strong machine learning fundamentals with substantial hands-on experience delivering end-user AI products. You should be comfortable moving between research, experimentation, production engineering, and collaboration with nontechnical stakeholders, while maintaining a strong focus on practical impact. /pulliStrong foundations in mathematics, deep learning, large language models (LLMs), and modern AI systems. /liliAt least 4 years of hands-on machine learning engineering experience, including building, evaluating, and systematically improving at least one end-user-facing product powered by deep learning. Experience limited to integrating model APIs, building internal dashboards, or contributing solely to ML infrastructure does not meet this requirement. /liliAt least 1–2 years of experience building LLM-powered applications, including at least one production-grade agent beyond a proof of concept. /liliPractical experience evaluating AI systems, with a strong understanding of dataset design, evaluation methodology, and performance measurement. /liliProficiency in Python and a willingness to remain deeply involved in hands-on implementation. /liliFluency in prompting and context engineering for agentic systems, including the ability to determine whether a problem requires improved prompting, a different model, better tools, or changes to the overall pipeline. /liliExperience using AI coding agents to produce high-quality work, with the judgment and accountability to validate outputs and take responsibility for what you ship. /liliAbility to read research papers, assess new ideas, and quickly test relevant approaches through practical experimentation. /liliAn experimental mindset, with the ability to reason carefully about data, models, and evaluation while making iterative, measurable progress. /liliStrong first-principles thinking and the ability to design practical, scalable solutions. /liliA user-focused approach that prioritizes whether a product works effectively for its intended audience. /liliProactive ownership,



urgency, attention to detail, and the ability to carry projects through to completion without constant direction. /liliStrong written and verbal communication skills, including the ability to explain technical concepts clearly to nonengineering audiences. /liliA commitment to responsible AI development and technology that delivers meaningful social benefits. /li /ulh3Bonus qualifications: /h3ulliExperience with multilingual natural language processing or low-resource languages, particularly Swahili, Hindi, and languages spoken across East Africa and South Asia. /liliPrevious work in global health, international development, or social-impact technology. /liliFamiliarity with behavioral science or AI applications designed to support behavior change. /liliExperience with data annotation pipelines and LLM evaluation methodologies. /liliKnowledge of AI safety, alignment, or responsible AI frameworks. /liliExperience deploying models in production and working with cloud infrastructure such as AWS, Google Cloud Platform, or Azure. /liliPublications at leading AI conferences or substantial technical writing documenting engineering research and results. /li /ulh3Benefits: /h3ullibCompensation: /b Competitive within the mission-driven technology sector, with compensation positioned below typical big-tech salary levels. /lilibRemote work: /b Fully remote, asynchronous-first working environment. /lilibFlexible schedule: /b Work hours can accommodate your time zone, with no mandated core hours. /lilibInternational collaboration: /b Join a globally distributed team working across North America, Europe, East Africa, East Asia, and South Asia. /lilibMeaningful impact: /b Build AI applications addressing practical challenges in healthcare, agriculture, and other areas of international development. /lilibTechnical ownership: /b Take projects from initial problem definition and model selection through deployment, evaluation, and continuous improvement. /lilibInterdisciplinary collaboration: /b Work alongside behavioral scientists, development economists, field researchers, and embedded engineers. /lilibOpen-source contributions: /b Share technical innovations, tools, and learnings with the wider community rather than keeping all work within proprietary products. /lilibProfessional development: /b Stay close to applied AI research and gain experience solving challenging problems in real operational environments. /lilibAutonomy and responsibility: /b Contribute within a small team with minimal hierarchy, direct feedback, and opportunities to influence technical decisions. /lilibLocation eligibility: /b The role is open to candidates based in Sub-Saharan Africa and South Asia. India falls within the stated eligible regions, subject to the hiring team's location and contracting requirements. /lilibContract arrangement: /b International hiring is conducted on a contractor basis. /li /ul #J-18808-Ljbffr

📌 AI/ML Engineer (Italia)
🏢 Jobgether
📍 Italia