Resume Keywords to Include
Make sure these keywords appear in your resume to improve ATS scoring
Sign up free to auto-tailor your resume with all these keywords and get a higher ATS score
Job Description
Role : Lead AI/ML Engineer with GCP
Location : Remote
Hire type : Contract
End Client - Banking client
Implementation partner - ********
Exp - 10+
- 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
--
Want AI-powered job matching?
Upload your resume and get every job scored, your resume tailored, and hiring manager emails found - automatically.
Get Started Free