Manager, Machine Learning Engineer

• 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