AI-ML Engineer
Indexed description
- Build and deploy ML and Generative AI solutions into production systems
- Productionize models using APIs, microservices, or batch pipelines
- Implement LLM-based systems (RAG, embeddings, evaluation, prompt optimization)
- Optimize performance, latency, cost, and reliability of AI services
- Maintain model monitoring, logging, and retraining workflows
- Work with data engineers to ensure data quality and availability
- Follow established MLOps, DevOps, and cloud standards
- Troubleshoot model, data, and infrastructure issues
background.
They are split into Minimum Qualifications (must have) and Additional Qualifications (nice to
have) along with soft skills (competencies) needed for the role:
Minimum Qualifications
- 4+ years of experience with large language models (LLMs) and natural language
- 3+ years of experience supporting and developing API/Microservices with Java, .Net or
- 3+ years of experience working with generative AI tools (e.g., OpenAI’s GPT, Anthropic
- 3+ years of experience working as developer with Python.
- 3+ years of experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
- 3+ years of experience working with relational databases (SQL)
- AI certifications
- ML certifications
- Cloud certifications (AWS, Azure)
- Demonstrated track record of working effectively within a collaborative and cohesive,
- Outstanding customer service and organizational skills
- Exceptional analytical, troubleshooting, and problem-solving skills
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search