GCP AI/ML Engineer
Role summary
We are seeking a Contract GCP AI/ML Engineer to design, build, and deploy machine learning models and AI-driven systems on Google Cloud. This role requires a blend of data science and software engineering expertise, focusing on creating scalable, production-ready solutions using tools like Vertex AI, TensorFlow, and BigQuery. Key responsibilities include developing and training models, implementing GCP services, automating MLOps pipelines, constructing data pipelines, integrating Generative AI, and optimizing deployed models. The ideal candidate will have 5+ years of experience in AI/ML deployment and software engineering, strong Python and SQL skills, and proven GCP expertise.
- Role : GCP AI/ML Engineer
Location : Remote/Canada
Hire type : Contract
- 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.
- Key Responsibilities
- - 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.
- Required Skills and Qualifications
- - 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.
- Preferred Qualifications
- - GCP Professional Machine Learning Engineer certification.
- Experience with Vertex AI agent builder
- Background in Natural Language Processing (NLP) or Computer Vision
