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Machine Learning Research Engineer

flagshippioneeringinc · Cambridge, MA USA · Iris Labs, Inc.
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<p><strong><span data-contrast="auto">The Company</span></strong><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">Iris Labs, Inc. is a privately held, early-stage company pioneering the use of artificial intelligence to transform how people navigate life’s challenges and wellbeing. We are creating a platform that empowers people to build a life they are proud of and fulfilled by. We bring together psychology, product, design, engineering, and machine learning to build digital experiences that are engaging, trustworthy, and genuinely helpful.  </span><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">Iris Labs is backed by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and builds companies that invent breakthrough technologies that transform the world. Flagship has created over 100 groundbreaking companies since 2000, including Moderna.</span> <br><span data-ccp-props="{}"> </span></p> <p><strong><span data-contrast="auto">The Role</span></strong><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">Iris Labs seeks a talented </span><strong><span data-contrast="auto">Machine Learning Research Engineer</span></strong><span data-contrast="auto">. The successful candidate will innovate, develop and apply machine learning (ML) methods to create foundational psychological tools. This position is ideal for someone with broad expertise in machine learning, reinforcement learning from human feedback, supervised fine tuning, and computational sciences who is looking to join a very dynamic and innovative environment and pioneer the next frontier of innovation, application, and human-ai interactions enabled by state-of-the-art models. A successful candidate should have a passion for building technologies that enable others to maximize their potential.</span><span data-contrast="auto"> </span><span data-contrast="auto"> </span><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">Working at Iris Labs, you will have the opportunity to work with world-class scientists, engineers, and researchers who work on cutting-edge ai research and applications. </span> <br> <br><strong><span data-contrast="auto">Key Responsibilities</span></strong><span data-ccp-props="{}"> </span></p> <ul> <li><span data-contrast="none"><span data-ccp-charstyle="normaltextrun" data-ccp-charstyle-defn="{"ObjectId":"ac0262f4-8a9e-5820-b908-2d943c5f7113|1","ClassId":1073872969,"Properties":[201342446,"1",201342447,"5",201342448,"1",201342449,"1",469777841,"Aptos",469777842,"Arial",469777843,"Aptos",469777844,"Aptos",201341986,"1",469769226,"Aptos,Arial",268442635,"24",469775450,"normaltextrun",201340122,"1",134233614,"true",469778129,"normaltextrun",335572020,"1",469778324,"Default Paragraph Font"]}">Design, develop, and deploy ML-powered applications that </span><span data-ccp-charstyle="normaltextrun">leverage</span><span data-ccp-charstyle="normaltextrun"> large language models (LLMs) to address complex challenges in wellbeing.</span></span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Collaborate with psychological experts and translate interdisciplinary insights into computational frameworks.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Help advance the state of the art in context engineering, agentic AI and learning from human feedback.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Build scalable pipelines for data collection, labeling, training, and deployment of LLM-based systems.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Support the integration of ML systems into real-world applications with measurable outcomes.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Communicate findings to a multi-disciplinary audience.</span><span data-ccp-props="{}"> </span></li> </ul> <p><strong><span data-contrast="auto">Professional Experience & Qualifications</span></strong><span data-ccp-props="{}"> </span></p> <ul> <li><span data-contrast="auto">Masters level (or above) experience in CS, ML, and AI is preferred, but can be relaxed for exceptional candidates.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Strong foundation in machine learning, deep learning, and natural language processing (NLP).</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Publications at top ML / NLP venues such as NeurIPS, ICML, ACL and EMNLP are a bonus.</span></li> <li><span data-contrast="none"><span data-ccp-charstyle="normaltextrun">Proven experience deploying LLM-powered applications in production environments, including </span></span><span data-contrast="none"><span data-ccp-charstyle="normaltextrun">expertise</span><span data-ccp-charstyle="normaltextrun"> in frameworks like </span><span data-ccp-charstyle="normaltextrun">PyTorch</span&gt

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