AI/ML Engineer
Tasks
- Architect scalable ML deployments
- Assess architectural trade offs prompting versus fine tuning
- Build PoCs validate feasibility and value
- Collaborate on data pipelines and feature engineering
- Communicate technical decisions to engineering and executive audiences
- Define monitoring drift detection and optimization standards
- Develop NLP CV audio and generative AI models
- Implement CI CD for ML automated training evaluation versioning and deployment
- Lead discovery workshops
- Lead fine tuning and PEFT methods
- Mentor engineers and guide research to production workflows
- Set coding standards and lead design reviews
- Stay current with foundation models and multimodal innovations
- Translate business challenges into AI/ML solutions
Perks/Benefits
Skills/Tech-stack
API Development | AWS SageMaker | Azure Machine Learning | CI/CD | Computer Vision | Diffusion Models | Docker | Generative AI | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Instruction Tuning | Kubernetes | Language Models | Large Language Models | LoRA | Machine Learning | Model Evaluation | Model Serving | NLP | PyTorch | Python | QLoRA | TensorFlow | Transformers | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Computer Science | Bachelor of Science in Information Technology
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
Regions
Countries
States
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