Gen AI

1 week ago

Bengaluru Chennai Pune, India Sonyo Management Consultants Full time US$ 1,20,000 - US$ 2,00,000 per year

Locations- PAN India

GenAI:


• Experience with AI and Machine Learning algorithms.


• Familiarity with AI platforms and understanding of their capabilities and limitations.


• Experience with Natural Language Processing (NLP).


• Understanding of RAG, neural networks, and other AI/ML concepts.


• Ability to design and implement AI models.


• Experience with AI/ML frameworks like TensorFlow, PyTorch, etc.

General Skills:


• Strong problem-solving skills.


• Excellent communication and teamwork skills.


• Ability to work in a fast-paced, dynamic environment.


• Strong project management and organizational skills.


• Ability to clearly and effectively present complex concepts to non-technicalLocation- PAN India

Exp- 5 to 12 Years

Key Responsibilities:

1. Design, implement, and maintain end-to-end ML pipelines for model training,

evaluation, and deployment

2. Collaborate with data scientists and software engineers to operationalize ML

models

3. Develop and maintain CI/CD pipelines for ML workflows

4. Implement monitoring and logging solutions for ML models

5. Optimize ML infrastructure for performance, scalability, and cost-efficiency

6. Ensure compliance with data privacy and security regulations

Required Skills and Qualifications:

1. Strong programming skills in Python, with experience in ML frameworks

2. Expertise in containerization technologies (Docker) and orchestration platforms

(Kubernetes)

3. Proficiency in cloud platform (AWS) and their ML-specific services

4. Experience with MLOps tools

5. Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.)

6. Knowledge of data versioning and model versioning techniques

7. Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack)

8. Knowledge of distributed training techniques

9. Experience with ML model serving frameworks (TensorFlow Serving, TorchServe)

10. Understanding of ML-specific testing and validation techniques

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