PL
GCP AI/ML Engineer
PeopleNTech LLC
🇺🇸 United States
On-site
6 months ago
- GCP
- AI/ML
- Machine Learning
- AI
- Natural Language Processing
- Vertex AI
- TensorFlow
- BigQuery
- Python
- PyTorch
- scikit-learn
- Dataflow
- Cloud Functions
- MLOps
- SQL
- RAG
- LangChain
- Devops
- Docker
- Kubernetes
- GKE
- CI/CD
- Computer Vision
6 months ago
Location : Remote
Rate : $65
Hire type : Contract
Indent: SF_OP_202199-4-1, SF_OP_202199-5-1, SF_OP_202199-6-1
- Detailed JD:
Responsible for designing, building, and deploying machine learning models and AI-driven systems within the Google Cloud ecosystem. This role bridges data science and software engineering, focusing on creating scalable, production-ready AI solutions—such as Generative AI, natural language processing, and predictive models—using tools like Vertex AI, TensorFlow, and BigQuery.
- Model Development & Training: Develop and train predictive and generative AI models using Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn, often within Vertex AI.
- GCP Implementation: Implement solutions using GCP services like BigQuery, Dataflow, Cloud Functions, and Vertex AI Pipelines to build scalable infrastructure.
- MLOps and Automation: Design and automate MLOps pipelines (training, deployment, monitoring) to ensure model performance, scalability, and reliability.
- Data Engineering: Construct data pipelines for ingestion, preprocessing, and storage of structured/unstructured data using SQL and BigQuery.
- Generative AI Integration: Implement LLMs, retrieval-augmented generation (RAG) patterns, and agentic workflows (e.g., using LangChain).
- Optimization & Troubleshooting: Monitor and optimize deployed models for accuracy, latency, and cost-effectiveness.
- Experience: 5+ years in AI/ML model deployment and software engineering.
- Technical Proficiencies: Strong programming skills in Python and SQL.
- GCP Expertise: Proven experience with Google Cloud Platform, specifically Vertex AI, Dataflow, and BigQuery.
- ML Frameworks: In-depth knowledge of TensorFlow, PyTorch, or Scikit-learn.
- DevOps/Containerization: Proficiency with Docker, Kubernetes (GKE), and CI/CD tools.
- Education: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.
- GCP Professional Machine Learning Engineer certification.
- Experience with Vertex AI agent builder
- Background in Natural Language Processing (NLP) or Computer Vision
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GCP AI/ML Engineer · PeopleNTech LLC