- 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
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Manager, Machine Learning Engineer Arbeitgeber: Jobtailor
Als Front Office Supervisor in unserem dynamischen Team bieten wir Ihnen die Möglichkeit, in einem unterstützenden und freundlichen Arbeitsumfeld zu wachsen. Wir legen großen Wert auf die berufliche Entwicklung unserer Mitarbeiter und bieten regelmäßige Schulungen sowie die Chance, Verantwortung zu übernehmen. Unsere Lage ermöglicht es Ihnen, Teil einer lebendigen Gemeinschaft zu sein, während Sie gleichzeitig die Standards unseres Franchise-Partners einhalten und unseren Gästen einen unvergesslichen Aufenthalt bieten.
