AI ML Engineer
VeeRteq Solutions Inc
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Remote
Tech stack
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Google BigQuery
Cloud Computing
Computer Programming
Continuous Integration
Data Flow Control
Python
Machine Learning
Natural Language Processing
Standard Sql
Strategies of Testing
Enterprise Search
Chatbots
Data Ingestion
Retrieval-Augmented Generation
Large Language Models
Prompt Engineering
Deep Learning
Generative AI
XGBoost
Machine Learning Operations
Terraform
Artificial Intelligence Markup Language (AIML)
GPT
Docker
Job description
- Design, develop, and deploy Generative AI solutions such as chatbots, virtual assistants, and enterprise search systems
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines and LLM-based intelligent applications
- Develop scalable machine learning models for healthcare and enterprise use cases
- Create end-to-end data and ML pipelines covering data ingestion, model deployment, and monitoring
- Optimize models for performance, accuracy, and cost efficiency
- Implement guardrails, evaluation frameworks, and testing strategies for GenAI systems
- Collaborate with business and technical stakeholders to translate requirements into AI-driven solutions
- Ensure scalable and reliable deployments on cloud environments
Requirements
Do you have experience in Terraform?, * Strong programming experience in Python and SQL
- Hands-on experience in Machine Learning (XGBoost, NLP, Deep Learning)
- Expertise in Generative AI (RAG, Prompt Engineering, Embeddings, Guardrails)
- Experience with LLM frameworks such as LangChain and LlamaIndex
- Cloud experience in AWS (Bedrock, SageMaker, S3) or GCP (Vertex AI, BigQuery, Dataflow)
- Exposure to MLOps tools (Airflow, CI/CD, Docker, Terraform)
- Proven experience in building and deploying production-grade AI/ML systems