AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | H[...]

Enigma; San Jose (CA); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Enigma in San Jose, CA seeks an AI Research Scientist focused on ML, DL, NLP, and LLMs. Hybrid work enables collaboration with research, engineering, and product teams to turn research into production-grade solutions. Ideal candidates hold a Ph.D.

(or M.S. with strong research/industry record), 3–5 years in AI/ML roles, and a track record of deployable research; publications are a plus. You will design experiments, develop reusable assets, and define evaluation protocols to ensure robust,

Qualifications

• Ph.D. strongly preferred in CS/AI or related field.
• Master’s degree with exceptional research or industry experience will be considered.
• 3–5 years in AI/ML research roles, ideally with deployed solutions.
• Publications in top AI/ML venues are a plus.

Responsibilities

• Design, execute, and analyze ML experiments with solid baselines and metrics.
• Stay current with AI research; adapt techniques for company use cases.
• Define evaluation protocols including offline metrics and adversarial testing.
• Specify data and annotation requirements; oversee quality control.
• Collaborate with researchers, product managers, and engineers to refine problems.
• Develop reusable research assets: datasets, code, eval suites, docs.
• Work with ML Engineers to optimize training and inference pipelines for production.
• Contribute to academic publications and research communities when needed.

Skills

Machine Learning

Deep Learning

Natural Language Processing

LLMs

PEFT/LoRA

RLHF/RLAIF

Python

PyTorch

Hugging Face

Experimentation

Education

Ph.D. in Computer Science / AI

M.S. with strong research/industry experience

Tools

PyTorch

Hugging Face

NumPy

Job description

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