Design, implement, and evaluate applied research projects to improve alignment, safety, and evaluation of LLM-based guardrails. Work on experiments (e.g., synthetic data quality metrics, explanations for blocked content), deliver results with mentor guidance, and present findings to the team to shape product capabilities.
About Alinia
Role Overview
Minimum Qualifications
Preferred Qualifications
Why Join Alinia?
We are an early-stage AI startup on a mission to enable the safe and compliant deployment of AI Agents in regulated industries, worldwide, through our Regulatory Guardrails & Auditing platform. We ensure conversational AI agents adhere to companies’ business policies and regulations at scale, like Investment Guard.
We envision a future where compliance is encoded in any autonomous system, steered by human experts. The goal is to augment compliance experts’ capabilities, empowering them to become key enablers in the deployment of AI Agents in the most critical scenarios at scale.
Co-founders Ari and Carlos come from leading ML platform at Twitter and LLM governance at Hugging Face.
At Alinia, our Applied AI Research Interns play a pivotal role in exploring new possibilities and capabilities for Alinia's Alignment Platform. This role demands a scientific mindset, a technical understanding of LLMs, and LLM development experience. We expect our interns to be self-motivated, action-oriented and hands-on. During the internship, interns will be expected to design, execute, and deliver their solutions to key challenges our customers encounter with the safe and responsible deployment of LLM applications. However, we don’t expect our interns to work alone. A mentor will be assigned throughout the internship to provide guidance, planning, and support. Interns will also be expected to participate in weekly meetings where they will share progress and present results. This role is designed for students who are ready to apply their expertise actively and decisively within a dynamic development environment.
Developing a robust and holistic alignment strategy and platform that combines state-of-the-art evaluation and optimization techniques, Responsible AI best practices and the realities of running a business is a complex task with applied research at the center.
As an Applied AI Research Intern at Alinia, you will experimentally design, develop, evaluate, and execute a project to support the training, evaluation, or use of Large Language Model (LLM)-based guardrails. Example projects include, but are not limited to:
- The development of a robust, automated approach to quantitatively measure synthetically-generated data quality.
- The incorporation of explanations for our LLM guardrails to provide post-hoc rationales for why content was blocked.
- Pruning and quantization of LLMs without sacrificing out-of-distribution performance.
We strive to create intern projects that provide the right mix of problem solving, learning, and real-world application as possible while also aligning with the student’s interests. As a member of a small team, this role presents a unique opportunity to make direct contributions to a real-world product. Your work will directly shape the art of the possible for our customers and their clients.
- MS student in Computer Science, AI, Linguistics, or a related field.
- Proven experience in LLMs, ML, or NLP.
- At least one publication in reputable AI, ethics, or machine learning conferences and journals.
- Strong programming skills in Python.
- Experience with ML frameworks such as TensorFlow, PyTorch, or JAX.
- Demonstrated knowledge and practical experience in LLM training (Please note: this is a strict requirement for the position).
- PhD student in Computer Science, AI, Linguistics, or a related field.
- Contributions to open-source projects or public datasets in the field of AI.
- First-author publications at peer-reviewed AI conferences.
- Experience with synthetic data generation, LLM as a judge frameworks, LLM post-training.
- Experience with explainable AI (XAI).
- Cutting-edge tech: Work on one of the most important challenges in AI—alignment, safety, and trust
- Flexible work: Hybrid or remote work, with preference for CET time zone
- Collaborative culture: Small, experienced, mission-driven team
- Impact: Directly shape the technical foundation of an AI governance platform adopted by enterprises
Similar Jobs
Security • Software • Cybersecurity • Automation
Enterprise Account Executive responsible for acquiring new enterprise customers, exceeding revenue quotas, building and managing an EMEA pipeline, developing partnerships, consulting senior executives, and accelerating SaaS buying processes. The role requires 7+ years of B2B SaaS sales experience, including new-business closing, enterprise account experience, and professional fluency in English plus French or German.
Top Skills:
Agentic AiSaaSSecurity And Compliance Software
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.
Top Skills:
LanggraphLlm ApisMlopsPydantic Ai
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Leads the vision, strategy, and execution of AI-powered data and analytics capabilities for Medical Affairs. Oversees patient journey analytics, advanced segmentation, stakeholder evaluation, data architecture, governance, and AI automation frameworks. Evaluates external innovations, builds proprietary solutions, manages analytics delivery teams, and advises senior leadership on data investments, innovation roadmaps, compliance, ethics, and competitive advantage.
Top Skills:
Advanced SegmentationAi/MlAutomation FrameworksData ArchitectureData GovernanceData ScienceHcp Network AnalysisHealthcare Data PlatformsPatient Journey Analytics
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
