Onto Innovation · 4 hours ago
Junior AI Engineer
Onto Innovation is a leader in process control, providing advanced technologies for semiconductor manufacturing. The Junior AI Engineer will collaborate with the AI Lead Engineer to develop AI solutions that enhance operational efficiency and support inspection and metrology tools.
3D TechnologyManufacturingSemiconductor
Responsibilities
Prototype AI assistants & agents for field workflows: guided recipe setup, log triage, playbook lookups, parts/alarms advice, and fleet-wide health checks
Build retrieval systems (RAG): ingest manuals, specs, ticket notes, recipes, logs, and best-practice docs; design chunking, embeddings, and indexing; tune prompts and retrieval for accuracy/latency
Connect AI to our tools and data: stand up MCP servers (Model Context Protocol) and other connectors to safely expose internal systems (document stores, MES, issue trackers, telemetry APIs) to LLMs
Fine-tune or adapt models (e.g., LoRA/QLoRA) for domain terms, error codes, and tool-specific intents when retrieval alone isn’t enough
Evaluate and harden: set up offline & online evals for groundedness/relevance; add guardrails, observability, and traceability; write runbooks
Ship small apps: package prototypes behind simple APIs or lightweight UIs that field engineers can use (web chat, Slack/Teams bots, or CLI)
Data plumbing: parse messy PDFs/images/CSVs; normalize schemas for recipes, events, alarms, SPC/trace data
Computer Vision – understanding, defect detection, segmentation, or SEM/optical imaging
Work like an engineer: write readable Python/TypeScript, tests, and docs; use Git; participate in code reviews; iterate fast with the AI lead and domain SMEs
Qualification
Required
BS in CS/EE/CE/ME (or equivalent experience)
Python proficiency (data wrangling, APIs, packaging); comfort on Linux and with Git
Built at least one LLM app using a framework such as LangChain, LlamaIndex, or Semantic Kernel
Hands-on with vector search (e.g., FAISS/Weaviate/Milvus) and embeddings; understands chunking, metadata, and hybrid search basics
Familiarity with RAG and prompt engineering; can measure quality (groundedness/relevance) and reduce hallucinations
Basic backend skills (REST/JSON, auth, environment secrets); experience containerizing with Docker
Comfortable reading technical manuals/logs and collaborating with non-software teammates
Preferred
Worked with agent frameworks (LangGraph, AutoGen, CrewAI) or implemented tool-calling/plan-execute loops
Built or configured MCP servers to connect LLMs to internal data/tools
Experience parsing complex docs (e.g., Unstructured, GROBID) and handling images/figures from manuals
Exposure to semiconductor equipment or factory systems (SECS/GEM, EDA/Interface A, MES, SPC); familiarity with KLA/AMAT/TEL/ASML tool ecosystems
Time-series and log analysis (Pandas, SQL, TimescaleDB/InfluxDB), wafer map/vision background, or simple CV
Model adaptation experience (LoRA/QLoRA, PEFT) and experiment tracking (MLflow/W&B)
LLM observability/evals (Ragas, TruLens, LangSmith), basic security/PII handling, and role-based access
Cloud familiarity (AWS/Azure/GCP) and lightweight front-ends (React/Next.js) for internal tools
Prior work on fleet-level dashboards/analytics or recipe/parameter management
Benefits
Health/dental/vision/life/disability
PTO
401K plan with employer match
Employee Stock Purchase Program (ESPP)
Health & wellness initiatives
Company
Onto Innovation
Onto Innovation stands alone in process control with our unique perspective across the semiconductor value chain.
Funding
Current Stage
Public CompanyTotal Funding
unknown1999-11-12IPO
Recent News
2025-12-22
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