Senior MLOps Engineer
Job Description
Join Edelman, a global leader in communications, as a Senior MLOps Engineer where you'll be at the forefront of AI innovation. This role offers an exciting opportunity to work with cutting-edge technologies including Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) techniques. You'll be responsible for designing and implementing scalable machine learning pipelines that power PR insights and automation.
The position requires 5+ years of experience and deep expertise in MLOps, working with modern data stacks and AI frameworks. You'll be part of a forward-thinking environment where you can make significant impact on projects that push the boundaries of AI-powered insights. The role involves working with state-of-the-art tools and technologies, including Databricks, cloud platforms, and container orchestration systems.
Edelman offers a competitive salary range of €65,000 - €80,000 annually, along with comprehensive benefits. The company strongly values diversity, equity, inclusion, and belonging (DEIB), creating an equitable and inspiring workplace that reflects the global community. This remote position offers flexibility while being part of a collaborative team focused on innovation.
The ideal candidate will combine technical expertise in ML/AI with strong communication skills and a collaborative mindset. You'll have the opportunity to work on challenging problems, implement cutting-edge solutions, and contribute to the evolution of AI applications in the communications industry. If you're passionate about AI/ML and want to make a meaningful impact while working with the latest technologies, this role offers an excellent opportunity for career growth and innovation.
Responsibilities For Senior MLOps Engineer
- Develop and maintain scalable MLOps pipelines for GenAI applications
- Deploy and optimize GenAI models, including LLMs in production environments
- Develop solutions using traditional AI techniques
- Implement and manage CI/CD pipelines for ML workflows
- Optimize cloud infrastructure for cost-efficient training
- Define and enforce best practices for model versioning and governance
- Monitor and troubleshoot production systems
- Utilize Databricks to build and manage data and ML pipelines
- Evaluate and integrate MLOps tools and frameworks
- Stay updated on GenAI technologies advancements
Requirements For Senior MLOps Engineer
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 5+ years of experience in MLOps, DevOps, or related roles
- Proven expertise in deploying and managing Generative AI models
- Proficient in Python and ML libraries
- Skilled in cloud platforms (AWS, GCP, Azure)
- Hands-on experience with Docker, Kubernetes, and container orchestration
- Expertise with Databricks
- Familiarity with MLflow, DVC, Prometheus, and Grafana
- Experience implementing security and compliance standards
- Strong problem-solving and communication skills
- Experience with support of junior team members
- Fluency in written and spoken English
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