Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Design and evaluate performance engineering tasks for AI training/evaluation. Optimize runtime, compilers, memory, CPU/GPU and concurrency. Produce documented solutions, evaluate AI-generated code, and build evaluation frameworks and scoring rubrics while collaborating with researchers and SMEs.

Design real-world ML and NLP tasks, build reference solutions and evaluation frameworks in Python, assess LLM outputs for correctness and reasoning, identify failure modes, create scoring rubrics, and collaborate with experts to improve model capabilities. Part-time, remote contractor (~20 hours/week).

Collect and evaluate Egyptian Arabic voice interactions for an AI voice assistant. Use a Mac to perform voice-driven tasks, record transcripts, clean transcripts, assess AI responses for quality, maintain logs, upload recordings, and follow project guidelines during a ~3-week remote engagement.

Evaluate and document AI voice assistant interactions in German using a Mac with Apple Silicon. Complete voice-based tasks, transcribe and polish spoken content, assess AI responses for quality, maintain task logs, and upload recordings and files for multilingual voice-data collection.

Remote full-time MLOps Engineer role to design, evaluate, and improve ML infrastructure and large-scale training systems. Develop and review challenging MLOps tasks, optimize GPU kernels (Pallas/Triton), create evaluation rubrics, and collaborate with researchers to improve model reasoning and training pipelines. Requires production JAX/PyTorch experience and strong distributed training knowledge.

Design real-world computer vision tasks, build reference solutions and evaluation components in Python, assess AI model outputs, identify failure modes, and develop structured rubrics and guidelines. Collaborate with experts to maintain high-quality training data and evaluation standards for multimodal and generative vision systems. Part-time, remote contractor role (~20 hours/week).

Evaluate and annotate physics content, create problem sets and technical documentation, and assess AI-generated responses for scientific accuracy. Contribute to dataset creation and provide expert feedback to improve AI model training. Collaborate remotely with project teams to ensure timely, high-quality deliverables and improve evaluation methodologies.

Contractor engineering SME to review and create technical engineering content for AI training: analyze documentation, develop examples and datasets, evaluate AI outputs for technical accuracy, and collaborate with teams to improve model performance and processes.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Contractor role to create original, high-quality financial documents (reports, analyses, models) with rich visuals (tables, charts, graphs) to train AI. Ensure accuracy, anonymize sensitive data, contribute long-form documents (10–100 pages), and clarify submissions as needed.