Company.ai · 19 hours ago
Artificial Intelligence Research Engineer
San Francisco Bay Area
Full-time
Hybrid
Mid, Senior LevelCompany.ai is building a network of category defining AI products in stealth-mode. The role involves designing and shipping agentic capabilities for vertical products, focusing on reliability, evaluation, and safety while optimizing for quick production and iteration.
Computer Software
Responsibilities
Invent and iterate on agent methods: tool planning, long horizon execution, retrieval and memory, preference learning, workflow decomposition, verification, and self correction
Build fast experiment loops: dataset creation, training runs, ablations, analysis, and next hypotheses
Own evaluation: automatic benchmarks, adversarial tests, human in the loop grading, reliability scoring, regression tracking
Ship to production: partner with product engineers, instrument behavior, run A B tests, improve real user success rates
Harden the system: failure mode discovery, mitigation, monitoring, and safe defaults
Qualification
Required
Strong ML foundation with a real track record: shipped systems, meaningful open source, or research output that moved something forward
Deep working knowledge of modern LLMs and transformers: tokenization, context management, KV cache behavior, decoding tradeoffs, scaling behavior
Hands on experience with tuning and alignment methods such as SFT, DPO, RLHF, reward modeling, RLAIF, preference data pipelines
Practical tool use expertise: function calling, schema design, structured outputs, validation, tool routing, retries, and tool error recovery
Reliability chops: hallucination reduction, calibration, self checking, verification, constraint driven generation, and safe fallbacks
Retrieval and memory experience: embeddings, RAG, reranking, chunking strategies, long context tradeoffs, memory that stays useful over time
Evaluation ownership: automated benchmarks, adversarial tests, human in the loop scoring, regression suites, and metrics that predict real user outcomes
Data craftsmanship: cleaning, deduplication, contamination checks, eval hygiene, synthetic data when appropriate, strong dataset discipline
Production readiness: instrumentation, A B testing, monitoring, on call quality, latency and throughput tradeoffs, cost aware iteration
Systems and infra competence: data pipelines, training jobs, experiment tracking, reproducibility, and debugging under real constraints
Strong product taste: you can simplify without losing power, and you care about the user experience as much as the model curve
Preferred
Experience with agent benchmarks, tool use, computer use, or multi step workflow execution
Experience with reliability research: verification, calibration, interpretability, safety testing
Experience with retrieval, memory, and personalization systems at scale
Which vertical you chose and why you think it can become inevitable at scale?
Benefits
Competitive salary and meaningful equity
Top tier tooling and compute for serious iteration
Relocation and immigration support when needed
Company
Company.ai
Company.ai is building a network of category defining AI products in stealth mode.
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase