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# Lead Machine Learning Engineer, Ads Research in Glendale

- **Company:** Energy Jobline
- **Location:** Glendale, CA, United States
- **Experience:** Expert
- **Salary:** $171,600.0 - $230,100.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Computer Vision, Computer Programming, Data Structures, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Pytorch, Large Language Models, Deep Learning, Information Technology, Data Analytics, Machine Learning Operations
- **Published:** August 4, 2026
- **Apply:** https://www.energyjobline.com/job/lead-machine-learning-engineer-ads-research-glendale-31337045

## About the Role

* Bachelor's in computer science or equivalent experience.
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 * Prior experience rigorously developing, researching, and/or productionizing any of the following generative AI modeling or AI-based editing domains: image, video, mixed media, audio, LLMs, or agentic flows.
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 * Experience creating ML datasets (especially in computer vision or generative AI) or developing rigorous quality evaluation processes or data labeling processes. Must include an appreciation for the importance of rigorous quality evaluation processes.
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 * Experience developing -processing applications via LLMs or agentic flows.
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 * Experience in rapid creative prototyping with generative AI is a plus, such as examples of rapid development of creative generative AI prototyping in research labs, hackathons, etc.
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 * Minimum 7 years of hands-on experience developing and deploying large-scale machine learning systems.
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 * Strong knowledge of AI/ML technologies, mathematics and statistics.
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 * Excellent communication, collaboration skills, and a strong teamwork ethic with both technical and non-technical audiences.
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 * Strong foundations in algorithms, data structures, and numerical optimization with experience in programming such as Python (primary), Java and SQL
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 * Familiarity with deep learning tools and frameworks such as TensorFlow, Pytorch, Jax, Hugging libraries etc.
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 * Expert knowledge with traditional (tabular) ML modeling and methods.
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 * Proven proficiency in deep learning methodologies, fine tuning, and transformer architectures.
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 * A proven track record of thriving in a fast-paced, data-driven, and collaborative work environment.
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 * Experience working closely with UX and front end designers building production generative AI products.



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