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. 
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 versatile Machine Learning & MLOps Engineer to join our team at Edelman. This role blends machine learning engineering and MLOps, enabling end-to-end AI development—from designing to deploying GenAI and traditional AI models. You will play a pivotal role in developing AI-driven solutions that 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 Us At Edelman, we believe in a collaborative and open environment 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:

• 3+ years of experience in machine learning and/or MLOps. 
• 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 (e.g., 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.

Edelman is committed to diversity, equity and inclusion and proud to be an equal opportunity employer. We welcome and encourage racially and ethnically diverse people, members of the LGBTQ community, veterans, parents, individuals with disabilities and members of any and all protected classes to apply.