Machine Learning Research Engineer

California

Machine Learning

200000

Permanent

Our client are a Series-A Software Company at the forefront of LLM innovation. They are hiring a Machine Learning Research Engineer to join their team and be responsible for spearheading state-of-the-art research to develop and enhance our agentic system. The successful candidate will play a pivotal role in creating new experiment ideas, optimizing product performance and driving innovation through advanced machine learning techniques.

Responsibilities:

As the ML Research Engineer, you will lead state-of-the-art research to develop and improve the agentic system.
Generate new experiment ideas to optimize product performance and enhance user experience.
Spearhead dataset collection, generation and optimization efforts to support model training and evaluation.
Own key technical areas including model/inference optimization, distributed training, fine-tuning, instruction fine-tuning, and multi-modal LLMs.
Collaborate closely with cross-functional teams to translate research findings into actionable insights and product enhancements.
Stay updated with the latest advancements in machine learning and related fields, and actively contribute to the company’s intellectual property through patents and publications.

Skillset:

PhD, Master’s or Bachelor’s degree in Computer Science, Engineering, Mathematics or similar.
At least three years of industry experience in machine learning research and development.
Demonstrated expertise in machine learning techniques, particularly in transformer-based systems.
Proven track record of impactful contributions to machine learning research, with at least one first-author publication in a reputable conference or journal.
Strong programming skills in Python and proficiency with machine learning libraries (e.g., TensorFlow, PyTorch).
Experience with large-scale dataset management, distributed computing, and cloud platforms (e.g., AWS, GCP).
Excellent problem-solving abilities and analytical thinking.