AI/ML Engineer – IoT Platform
A global technology company is seeking an experienced AI/ML Engineer to help build an AI-driven IoT platform that transforms raw device data into actionable insights.
This role involves developing and deploying machine learning and generative AI (LLM/RAG) models for real-world industrial IoT use cases, such as smart factories, logistics, and energy management. The ideal candidate will have strong experience in end-to-end ML system design, time-series data processing, and scalable model deployment in production environments.
Salary
$ 100K-150K / year
Job Location
San Jose / Remote, CA
Type of employment
Full time
Language
English, Japanese
Work hours
TBA
Remote Work
○
Industry
Information Technology and Services
Visa Sponsor
NO
Posted
1 day ago
Job ID
#1593
Benefits
Competitive employee benefits package
(Insurance, Sick Leave, Paid Vacation etc)
Responsibilities and Duties
- Design and develop ML and LLM/RAG models to power insights beyond chatbots—such as anomaly detection, forecasting, and recommendations.
- Own the end-to-end ML workflow: data curation, feature engineering, model training, evaluation, deployment, and monitoring with measurable KPIs.
- Implement robust retrieval pipelines and prompt flows using modern frameworks (e.g., LangChain, LlamaIndex).
- Collaborate with product and UX teams to translate business requirements into measurable AI/ML outcomes.
- Drive continuous improvement through A/B testing, error analysis, and experiment tracking.
- Manage cloud-based ML infrastructure (e.g., GCP, AWS, or Azure) and ensure scalable data pipelines for IoT/time-series data.
Qualifications
- Bachelor’s degree or higher in Computer Science or a related field.
- A portfolio (e.g., GitHub, demos, or case studies) demonstrating relevant ML/AI project experience.
- 5+ years of hands-on experience building and operating ML models end-to-end.
- 3+ years of practical experience with generative AI (LLMs/RAG).
- 5+ years of experience in industrial or enterprise IoT environments.
- Strong proficiency in TensorFlow and related ML libraries.
- Familiarity with LangChain/LlamaIndex, vector databases (Pinecone, Milvus, Weaviate, etc.), and BigQuery ML or equivalent.
- Experience with time-series data, anomaly detection, and streaming ETL for IoT systems.
- Solid understanding of MLOps tools (e.g., MLflow, W&B) and API protocols (REST, GraphQL, MQTT).
- Strong documentation and communication skills for cross-functional collaboration.
- Knowledge of data security, access control, and compliance best practices are preferred.
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