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Tech Stack
Tools & technologiesAzureCloudGoogle Cloud PlatformLinuxPython
About the role
Key responsibilities & impact- Design, develop, and deploy Generative AI and machine learning solutions using large language models and modern AI frameworks.
- Implement LLM fine-tuning, prompt engineering, retrieval-augmented generation (RAG), and model optimization techniques.
- Deploy and manage AI/ML pipelines and GenAI applications in production environments using cloud platforms such as Azure or GCP.
- Build and maintain agentic AI systems leveraging modern orchestration and agent frameworks.
- Work with large datasets to build data pipelines and ensure effective model training and evaluation.
- Develop AI solutions using Python and modern ML libraries.
- Manage deployments and infrastructure in Linux-based environments.
- Ensure secure processing and governance of sensitive data, including PII and PHI, adhering to enterprise security and compliance standards.
- Optimize AI models and infrastructure for performance, scalability, reliability, and cost efficiency.
- Collaborate with cross-functional teams to integrate AI models into enterprise applications and production systems.
- Document model architectures, experiments, deployment pipelines, and operational processes.
- Stay current with emerging developments in Generative AI, LLMs, and AI engineering practices.
Requirements
What you’ll need- Bachelor’s degree in Engineering, Computer Science, AI/ML, Data Science, or a related technical field
- 10+ years of overall professional experience in software engineering, machine learning, or AI engineering.
- Minimum 3+ years of hands-on experience working with Generative AI technologies and LLMs.
- Strong programming experience in Python.
- Proven experience fine-tuning, deploying, and optimizing large language models.
- Experience deploying Generative AI solutions into production environments.
- Hands-on experience working with Linux-based systems.
- Experience with cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP).
- Experience building ML pipelines and deploying AI models using modern MLOps practices.
- Experience handling and securing sensitive data such as PII and PHI in compliance with security and regulatory requirements.
Benefits
Comp & perks- Health insurance
- Flexibility in working hours
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Generative AImachine learninglarge language modelsLLM fine-tuningprompt engineeringretrieval-augmented generationmodel optimizationPythonMLOpsdata pipelines
Soft Skills
collaborationcommunicationproblem-solvingorganizational skillsadaptability
Certifications
Bachelor’s degree in EngineeringBachelor’s degree in Computer ScienceBachelor’s degree in AI/MLBachelor’s degree in Data Science
