AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | Hybrid | San Jose, CA

AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | Hybrid | San Jose, CA

Responsibilities:

• Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics.

• Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases.

• Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness.

• Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes.

• Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints.

• Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation.

• Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems.

• Contribute to academic publications and represent the company in research communities, as needed.

Educational Qualifications:

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred.

• Candidates with a master’s degree and exceptional research or industry experience will also be considered.

Industry Experience:

• 3–5 years of experience in AI/ML research roles, ideally in applied or product-focused environments.

• Demonstrated success in delivering research-driven solutions that have been deployed in production.

• Experience collaborating in cross-functional teams across research, engineering, and product.

• Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus.

Technical Skills:

• Strong foundational knowledge in machine learning and deep learning algorithms.

• Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO).

• Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases.

• Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations.

• Advanced programming skills in Python (preferred), C++, or Java.

• Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc.

• Strong mathematical foundations in probability, linear algebra, and calculus.

• Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc.

• Ability to translate research insights into roadmaps, technical specifications, and product improvements.

AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | Hybrid | San Jose, CA