Machine Learning & MLOps Engineer

Edelman is a voice synonymous with trust, reimagining a future where the currency of communication is action. Our culture thrives on three promises: boldness is possibility, empathy is progress, and curiosity is momentum. At Edelman, we understand diversity, equity, inclusion and belonging (DEIB) transform our colleagues, our company, our clients, and our communities. We are in relentless pursuit of an equitable and inspiring workplace that is respectful of all, reflects and represents the world in which we live, and fosters trust, collaboration and belonging.We are seeking a versatileMachine Learning & MLOps Engineerto join our team at Edelman. This role blendsmachine learning engineering and MLOps, enablingend-to-end AI development—from designing to deployingGenAI and traditional AI models. You will play a pivotal role in developingAI-driven solutionsthat deliver actionable PR insights. This role is ideal for someone who enjoys prioritizing speed and impact, using existing tools and frameworks to accelerate development and deployment. Why You'll Love Working with UsAt Edelman, we believe in acollaborative and openenvironment where every team member’s voice is valued. Data and AI are central to our future, and you’ll be part of a team shaping it. You’ll thrive here if you're passionate about rapid prototyping, client focus, solving complex challenges, and working in a supportive, forward-thinking team. 

Key Responsibilities:

Quickly develop and iterate on MLOps pipelines for GenAI applications, focusing on rapid deployment and continuous improvement.  Deploy and optimize GenAI models, including LLMs such as GPT, using existing frameworks to accelerate time to production.  Leverage traditional AI techniques (decision trees, clustering, regression) to enhance GenAI workflows, choosing pragmatic solutions over overly complex approaches.  Implement and manage lightweight CI/CD pipelines for ML workflows, prioritizing fast testing, validation, and deployment.  Optimize cloud infrastructure for cost-efficient and scalable training and serving of GenAI and LLM models, without unnecessary overhead.  Define practical best practices for model versioning, reproducibility, and governance, ensuring efficiency without excessive rigidity.  Monitor and troubleshoot production ML systems proactively, minimizing downtime with quick fixes and iterative improvements.  Evaluate and integrate state-of-the-art MLOps tools that provide the fastest and most effective path to production for LLMs and GenAI models.  Stay updated on advancements in GenAI technologies, including LLM fine-tuning and serving, and apply practical innovations to accelerate development. 

Technical Requirements:

Experience deploying production-ready ML models, including LLMs, time series, and tabular models.  Strong experience with OpenAI’s custom GPTs and Assistants API, including Actions, function calling, and API integrations.  Capability in designing and implementing API-based interactions within LLM applications, including retrieval-augmented generation (RAG) and vector database integration.  Exposure to LLM fine-tuning (OpenAI, Hugging Face) and prompt optimization for production.  Understanding of ML pipelines, CI/CD, and cloud platforms for model deployment.  Proficiency with Python and experience in ML frameworks (, TensorFlow, PyTorch, Hugging Face Transformers).  Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, Git, Databricks).  Bonus: Experience working with media metrics, behaviors, and AI-driven insights is a plus. 

Non-Technical Requirements:

Clear and friendly communication skills. Excellent problem-solving skills and attention to detail. Strong communication skills. A team player who thrives in Agile environments.

#LI-RT9We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your experience doesn’t perfectly align with every qualification, we encourage you to apply anyway. You may be just the right candidate for this or other roles.