AI/ML Engineer - NLP Scientist
Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Oct 12, 2026.
Our client, a world leader in biotechnology and life sciences, is looking for a “Senior AI/ML Engineer - NLP Scientist ”.
Location: South San Francisco, CA
Job Duration: Long-Term Contract (Possibility Of Extension)
Rate: $80-$85/hr on W2
Company Benefits: Medical, Paid Sick Leave, 401 (k)
We are seeking aSenior AI/ML Engineerto build an evidence-grounded AI capability that verifies generated claims against approved scientific, clinical, regulatory, and reference materials before human review. The system will retrieve relevant evidence, decompose claims into verifiable assertions, evaluate evidence support, and providetraceable decisions with citations. The system must recognize unsupported or contradicted claims andabstain rather than guess.
Key Responsibilities
Build production-gradePython/NLP pipelinesfor claim verification and evidence attribution.
Develophybrid retrievalusing lexical and vector search to identify relevant evidence.
Implementclaim decomposition, natural language inference (NLI), entailment, and contradiction detection.
Evaluate whether generated claims are genuinely supported by cited evidence.
Designconfidence thresholds, abstention logic, escalation rules, and human-in-the-loop workflows.
Build evaluation datasets with expert annotation guidelines and measureinter-annotator agreement.
Track false approvals, false rejections, abstentions, and other error categories.
Develop traceable systems that allow decisions to be reconstructed based onmodel version, evidence, citations, and reviewer actions.
Work with Medical, Legal, Regulatory, and scientific stakeholders to translate review requirements into technical solutions.
Required Skills
StrongPythonproduction engineering.
NLP / LLM / Generative AIdevelopment.
RAG, hybrid search, vector search, and lexical retrieval.
Natural Language Inference (NLI), entailment, contradiction detection.
Claim decomposition and evidence attribution.
LLM/model APIs and production evaluation frameworks.
AI/ML evaluation, benchmarking, and error analysis.
Human-in-the-loop AI,confidence scoring and abstention.
Experience with scientific, technical, regulatory, legal, or other high-stakes content.
Experience creatingexpert-labeled datasets and annotation guidelines.
Strong understanding oftraceability, citations, and reproducible AI decisions.
Preferred Skills
Knowledge graphsand relationships between claims, evidence, references, products, and indications.
Deterministicrules + ML/LLM decision systems.
Pharmaceutical, biotech, healthcare, regulatory, legal, financial compliance, or scientific
publishing experience.
Familiarity withclinical studies, statistics, scientific literature, and citation practices.
Experience withLangChain, LlamaIndex, Hugging Face, PyTorch, or similar NLP/
LLM frameworks.
If interested, please share your updated resume at[email protected] / [email protected]