Manager, Machine Learning Engineer

Darum lohnt es sich

• Lead a team of 6 ML engineers to bring state of the art AI to Clio's clients, spanning traditional ML models, GenAI, and agentic AI. • Guide the team in designing and shipping agentic systems, including retrieval, tool use, orchestration, and the evaluation frameworks that keep them reliable and safe in production. • Collaborate cross-functionally with MLOps engineering, product management, operations, and data science to identify new tooling for ML and LLM-driven features for Clio customers. • Work in an agile environment with our team of ML engineers, ML ops, and full stack developers across a variety of projects. • Learn new things, challenge yourself, and hone your craft as an ML and infrastructure expert in a space that is moving fast. • Participate in diverse projects and collaborate with multiple engineering teams across three countries. • Review and provide feedback on code, both from within your own team or across all of Clio. • Collaborate with teams across Clio to diagnose, understand, and solve problems, and to build solutions that may span many areas. • Teach and learn from those around you, providing constructive feedback and taking on feedback to help grow.

Requirements • Experience in managing high performing teams (6+ ML Engineers). • Experience with technical evaluations of various ML and LLM products, vendors, out-of-the-box solutions, and conducting quick proof of concepts if necessary. • In-depth understanding of LLMs, GenAI, and the competitive landscape, including where the technology is heading. • Hands-on familiarity with building agentic systems, such as tool-calling agents, RAG pipelines, prompt and context design, and evaluating agent behavior at scale. • Experience in fine-tuning foundational models and/or training language models in-house. • Experience to manipulate, clean, and pre-process complex unstructured data for model development. • The ability to become fluent in new technologies quickly and work effectively in an ever-evolving environment that includes distributed teams and customers. • Demonstrated success in mentorship in software development, particularly using an Agile process and with large scale SaaS products. • A diverse base of knowledge that allows you to help your team solve complex technical problems. • A history of past projects (including notable successes and lessons learned). • Clear and concise communication skills and the ability to build high-trust relationships with fellow Clions and customers.

Core Competencies Demonstrates expertise in managing high-performing teams of ML engineers, with a strong focus on building and evaluating agentic systems and LLMs. Proficient in collaborating cross-functionally to drive innovative ML solutions and mentoring team members in an agile environment.

Highest-signal resume keywords • Team Leadership • Agentic Systems Development • LLM Fine-Tuning • Technical Evaluation of ML Products • Agile Methodologies ATS Optimization Keywords Hard Skills • Machine Learning • Large Language Models • GenAI • Data Pre-Processing • Model Training • Tool-Calling Agents • RAG Pipelines • Prompt Design • Context Design • Code Review Soft Skills • Clear Communication • Mentorship • Problem Solving • Collaboration • Feedback Reception Industry Keywords • SaaS Products • Agile Process • MLOps • Cross-Functional Collaboration • Distributed Teams