AI/ML Engineer — End-to-End ML, Research to Deployment

Digitailor; Foster City (CA); Sur place; USD 180 000 - 250 000; Plein temps

Avantages offerts par ce poste

Equity

Benefits

Résumé du poste

Conviva is seeking an AI/ML Engineer to design, develop, train, and evaluate machine learning models for real‑world challenges. You will own the end‑to‑end ML lifecycle, from data prep to deployment, and explore modern techniques including deep learning and LLM tuning.

The role emphasizes collaboration with engineering and product teams to create scalable experimentation and robust ML systems, with a path for PhD graduates or researchers to contribute at a high level.

Qualifications

• PhD preferred in Computer Science, ML, Mathematics or Statistics.
• Hands-on experience developing and evaluating ML models in research or industry.
• Strong foundation in ML fundamentals, statistics, and data structures.

Responsabilités

• Design, develop, train, and evaluate machine learning models to solve real‑world problems.
• Own end‑to‑end ML development lifecycle: data prep, model design, training, evaluation, and iteration.
• Explore modern ML techniques including deep learning, RL, and LLM fine‑tuning as appropriate.
• Collaborate with engineering and product teams to deploy scalable ML solutions.
• Contribute to ML tooling, data pipelines, and infrastructure for experimentation.

Connaissances

Machine learning

Deep learning

Probability

Statistics

Algorithms

Data structures

Python

C++

Model development

Formation

PhD in Computer Science / ML / Mathematics / Statistics

Outils

PyTorch

TensorFlow

Python

C++

Description du poste

Conviva is seeking an AI/ML Engineer to design, develop, train, and evaluate machine learning models for real‑world challenges. You will own the end‑to‑end ML lifecycle, from data prep to deployment, and explore modern techniques including deep learning and LLM tuning.

The role emphasizes collaboration with engineering and product teams to create scalable experimentation and robust ML systems, with a path for PhD graduates or researchers to contribute at a high level.