A high-growth organization in the advertising technology space is looking to build and scale the next generation of its machine learning platform
Requirements
- Skilled in MLOps, ML automation, and designing scalable ML infrastructure.
- Hands-on deep learning practitioner with experience in PyTorch (ideally PyTorch Lightning) and familiarity with LLM tooling.
- Strong cloud infrastructure background with AWS, Docker, and orchestration tools like Airflow.
- Comfortable working with large-scale datasets.
- Experienced senior engineer with a strong record of delivering complex systems end-to-end.
- Familiarity with LLMs, Hugging Face ecosystem
- Experience with distributed data processing tools
Responsibilities
- Own the end-to-end ML lifecycle, including data exploration, model development, deployment, monitoring, and continuous improvement.
- Build and maintain scalable data pipelines and infrastructure that support automated training, evaluation, and model lifecycle management.
- Redesign and optimize existing systems to solve scalability challenges and streamline complex workflows.
- Collaborate closely with product, engineering, operations, and ML teams to improve process efficiency and system performance.
- Take ownership of core codebases and provide mentorship to junior engineers.
- Languages & Frameworks: Python (primary), PyTorch Lightning
- Cloud & Infrastructure: AWS, Docker, Apache Airflow
Other
- Strong communicator who collaborates well across technical and non-technical teams
- Strategic thinker who also executes hands-on.
- AdTech or startup environment experience
- Hybrid work environment (3x/wk onsite) in Bellevue, WA or San Mateo, CA
- Strong engineering fundamentals
