Back
Tier-1 brand, mid-level ML title, metro location, and broad ML skillset drive high competition.
Advanced ML and production experience transfer broadly, but creative/marketing domain experience increases specificity.
Explicit 5+ years (or PhD+2) plus mandatory production ML, PyTorch, and cloud experience.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end development, training, deployment, and iteration of machine learning models and pipelines for vision, video, and language creative understanding.
Build and deliver scalable ML pipelines including ingestion, featurization, training, versioning, and inference in production environments (Spark, Kubernetes, GPU/CPU).
Validate models via offline benchmarks and online A/B testing; collaborate cross-functionally with product managers, research scientists, and engineers to link ML outputs to customer value.
Master's degree with 5+ years relevant experience, or PhD with 2+ years, or equivalent impact.
Experience shipping ML models to production with demonstrable product or business impact.
Strong Python and PyTorch skills for model development and deployment.
Experience in deep learning for vision, video, NLP, or generative AI (including LLM/VLM fine-tuning and embeddings). Distributed data processing and cloud platforms experience (Spark, Kubernetes, GCP, AWS, or Azure).
Able to independently lead and execute well-scoped ML problems with limited supervision, showing strong ownership.
Experienced in end-to-end ML systems: feature engineering, training pipelines, inference, and production monitoring.
Works effectively across teams and communicates ML trade-offs and technical direction clearly to diverse partners.