Develops ML models and workflows for generating simulation scenarios in autonomous vehicle testing, integrating LLMs/VLMs, collecting data for fine-tuning, and collaborating with teams to enhance safety validation. Requires MS/PhD, 2+ years ML experience, and Python/PyTorch proficiency.
151k – 257k
Hybrid2+ YOEML Engineering
About the role
Responsibilities
Integrate and validate LLMs/VLMs and implement other models for complex scenario generation workflows, leveraging techniques like advanced prompting, agentic tool use, and more.
Contribute to tooling for AI-based scenario understanding and validation.
Collect data and design metrics to drive business intelligence, product iteration, and model fine-tuning.
Collaborate directly with internal customers and partner teams to provide generative AI solutions for their test creation workflows.
Directly contribute to the safety and reliability of autonomous software.
Qualifications
MS or PhD in Computer Science, Machine Learning, or related field
2+ years of industry experience in Machine Learning
Solid understanding of LLM or NLP concepts
Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
Bonus Qualifications
Practical experience in dataset creation for fine-tuning, system integration of ML models into production, or optimization techniques for low-latency inference systems
Familiarity with autonomous vehicles, robotics, and/or complex simulation environments
Hands-on experience in areas like program synthesis, diffusion models, and/or formal methods/V&V
Relevant publications in conferences (e.g., CVPR, ICCV, RSS, and/or ICRA)
Quantitative Researcher developing cutting-edge ML and statistical models to identify predictive signals in global financial markets. Requires PhD in a STEM field, strong Python skills, and interest in ML/AI; no finance experience needed. Matched to Alpha Research, Data Science, or Strategy Research teams.
150k – 200k
On-siteEntry levelML Engineering
AI Engineer, Evaluation
Distyl AISan Francisco, CA +1
Design and implement evaluation frameworks and pipelines for AI systems using Evaluation-Driven Development. Build Python-based test suites, LLM graders, and measurement systems that guide prompt iteration and production deployment decisions.
150k – 250k
Hybrid2+ YOEML Engineering
AI Engineer - Data Intelligence
ClariumUnited States
As an AI Engineer, you will build and maintain Clarium's master data enrichment pipeline, focusing on classification and entity resolution workflows. You will write production Python and SQL code, analyze complex datasets, and proactively audit data for quality issues.
150k – 180k
RemoteEntry levelML Engineering
Forward Deployed Engineer
Bretton AISan Francisco, CA
Forward Deployed Engineer deploys AI agents for financial services customers, handles onsite integrations in regulated environments, builds connectors and frameworks, and translates customer needs into product insights. Requires 2+ years software engineering with Python, APIs, data pipelines, cloud, and AI experience.
150k – 200k
On-site2+ YOEML Engineering
Early Career Research Engineer
ParallelPalo Alto, CA +1
Designs and trains embedding and retrieval models for AI agents to access web data at hyperscale, balancing research innovation with production efficiency for sub-second latency and fresh indexes.