Anori is an Alphabet X spinout building a platform to streamline pre-development permitting and approvals for buildings.
<p><strong>The Team:</strong></p> <p>We are an early stage geoscience AI team at X with a growing, interdisciplinary portfolio. To prove our path to the moon, we make early contact with the real world through both internal and external partnerships. As a member of the team, you are a self-starter, have a deep passion for problem solving and experimentation and will work on 0-1 AI-based products. </p> <p><strong>The Role:</strong></p> <p>As a ML Engineer, you’ll be instrumental in translating cutting-edge multi-modal AI research into real-world products. You will harness multi-modal foundation models to drive real-world, high-impact outcomes. Additionally, you’ll contribute significantly to centralized scalable training and eval infrastructure.</p> <p><strong>How you will make 10x impact:</strong></p> <ul> <li>Act like an owner; be fearless in diving deep, asking questions, proposing solutions, establishing consensus and then making things happen.</li> <li>Define ML experiments, perform data reviews, train and test various multimodal ML architectures.</li> <li>Extensive use of AI for code tooling.</li> <li>Get your hands dirty! Identify, design, and implement a set of experiments and move them to MVPs. </li> <li>Have fun, learn from your teammates and teach them as well!</li> </ul> <p><strong>What you should have:</strong></p> <ul> <li>MS/PhD in CS or equivalent practical experience in ML, and <strong>6+ years of professional experience building and releasing production software</strong> <strong>(in <span style="text-decoration: underline;">addition</span> to internships)</strong></li> <li>3+ years of hands-on industry experience in AI research, scalable model training, evals, and model deployments. Experience with multi-model models is strongly preferred.</li> <li>We particularly value experience in <strong>early-stage or startup environments</strong>, where engineers take ownership and drive product development from the ground up.</li> <li>ML Ops experience - setting distributed training and eval pipelines. Hands-on experience building scalable data pipelines and managing ML workflows.</li> <li>Substantial experience with machine learning frameworks and libraries, such as PyTorch, Hugging Face, or TensorFlow.</li> <li>Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform).</li> <li>Experience using AI code generation tools.</li> <li>Strong Python proficiency.</li> </ul> <p>The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.</p> <p>Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.</p>