Job description:
Title: Generative AI Engineer – NLP & Machine Learning Specialist
1. List of Skills
Category
Skills
Strong Expertise
- Generative AI Model Development
- Natural Language Processing (NLP)
- Machine Learning & Deep Learning
- Python Programming for AI Development
- Model Fine-Tuning & Optimization
- AI Model Deployment & MLOps (Docker, Kubernetes, CI/CD)
- Data Science & Statistics
- SRE Monitoring Tools Integration & Usage
- Development for SRE Observability (Prometheus, Grafana, ELK, Datadog, New Relic, Splunk, etc.)
- Incident Response Automation & Reliability Engineering
Basic Proficiency
- Large Language Models (LLMs) & Open-Source AI Frameworks
- Data Engineering & Data Processing (Apache Spark, Pandas, NumPy, PyTorch, Scikit-learn, TensorFlow)
- Conversational AI & Chatbot Development (LangChain, AutoGen)
- Cloud AI Platforms (GCP, AWS, Azure)
- Alerting & Monitoring Pipeline Development (Opsgenie, PagerDuty, ServiceNow, etc.)
- Infrastructure as Code (Terraform, Ansible) for SRE Automation
Knowledge Only
- Open-Source Contributions in AI
- Software Design Principles & Architecture
- AI Ethics & Bias Mitigation
- SRE Best Practices & Reliability Patterns
2. Primary Skills
- Generative AI Model Development
Design, develop, and deploy state-of-the-art generative AI models, including open-source LLMs, tailored for specific business needs. - Natural Language Processing (NLP)
Implement advanced NLP techniques such as text generation, summarization, translation, and sentiment analysis for AI-driven solutions. - Machine Learning & Deep Learning
Apply cutting-edge ML and deep learning algorithms to enhance AI model accuracy and efficiency in real-world applications. - Python Programming for AI Development
Strong proficiency in Python (or R/Java) for developing and implementing AI models, leveraging frameworks like Hugging Face, OpenAI GPT, spaCy, and NLTK. - Model Fine-Tuning & Optimization
Customize pre-trained AI models for domain-specific use cases, optimizing them for performance, scalability, and efficiency. - AI Model Deployment & MLOps
Develop, deploy, and maintain AI models in production environments using FastAPI, Django, and MLOps tools such as Docker, Kubernetes, and CI/CD pipelines. - SRE Monitoring Tools Integration & Usage
Integrate and develop application-level monitoring using SRE tools (Prometheus, Grafana, ELK, Datadog, New Relic, Splunk, etc.) to ensure observability, reliability, and performance of deployed AI solutions. - Incident Response Automation & Reliability Engineering
Implement automated incident response workflows, reliability engineering practices, and participate in on-call rotations to maintain high availability and resilience of AI applications.
3. Secondary Skills
- Large Language Models (LLMs) & Open-Source AI Frameworks
Experience with LangChain, AutoGen, and other frameworks to build scalable AI solutions that leverage large-scale pre-trained models. - Data Engineering & Data Processing
Work with data processing frameworks such as Apache Spark, Pandas, PyTorch, NumPy, Scikit-learn, and TensorFlow to prepare high-quality training datasets. - Conversational AI & Chatbot Development
Develop intelligent chatbots and conversational AI applications using NLP techniques, integrating with business applications. - Cloud AI Platforms (GCP, AWS, Azure)
Strong knowledge of cloud platforms to deploy and scale AI applications efficiently in cloud environments. - Alerting & Monitoring Pipeline Development
Build and maintain alerting pipelines using SRE tools (Opsgenie, PagerDuty, ServiceNow, etc.) for proactive incident detection and resolution. - Infrastructure as Code for SRE Automation
Use Terraform, Ansible, and similar tools to automate deployment and monitoring infrastructure for AI applications. - Open-Source Contributions in AI
Actively contribute to open-source AI projects, improving and innovating existing LLMs and generative AI technologies. - AI Ethics & Bias Mitigation
Awareness of AI fairness, ethical considerations, and techniques to mitigate biases in generative AI models.
