class MLEngineer:
def __init__(self):
self.name = "Anurag Trivedi"
self.role = "Machine Learning Engineer @ SAXONY.ai"
self.location = {
"city": "Dresden",
"country": "Germany"
}
self.expertise = {
"ml_ai": [
"LLMs (LLaMA3, Mistral, OpenAI, Claude.ai, Google gemini)",
"RAG Pipeline Development",
"Knowledge Graphs",
"Computer Vision",
"NLP Research",
"Drug Discovery"
],
"mlops": [
"Docker", "Kubernetes",
"AWS SageMaker", "GCP",
"MLflow", "ClearML"
],
"tools": {
"frameworks": ["PyTorch", "TensorFlow", "LangChain", "LlamaIndex"],
"databases": ["Neo4j", "MongoDB", "AstraDB", "Qdrant", "Milvus"],
"languages": ["Python", "SQL", "C++", "R", "JavaScript"]
}
}
def get_achievements(self):
return {
"performance_improvements": {
"operational_costs": "40% reduction",
"model_accuracy": "35% improvement",
"user_engagement": "40% increase",
"query_accuracy": "30% improvement",
"hallucination_reduction": "45% decrease"
},
"key_projects": [
"Enterprise-grade conversational AI system",
"Dual-LLM validation architecture",
"Code-to-code-text RAG pipeline",
"Vision Language Model for construction",
"Digital twin system for hydrogen fuel cells"
]
}
def get_certifications(self):
return [
"Udacity Agile Software Development Scholar",
"MIT Micro Master in Machine Learning",
"IBM Quantum Machine Learning Summer School",
"ETH Zurich Quantum Information For Developers"
]
def get_bio(self):
return """
π¬ Results-driven Machine Learning Engineer with 3+ years of expertise in AI/ML
π§ͺ Specialized in Drug Discovery using computational techniques
π€ Building enterprise-grade AI systems with LLaMA3, Mistral, Claude.ai
π Reduced operational costs by 40% through innovative MLOps solutions
π― Improved model accuracy by 35% using advanced fine-tuning methods
π Silicon Saxony Hackathon 2024 - AI-powered Skat game assistant
"""
me = MLEngineer()
print(me.get_bio())
π§ Machine Learning & AI
- Large Language Models (LLMs)
- Natural Language Processing
- Computer Vision
- Reinforcement Learning
- Neural Networks Architecture
𧬠Drug Discovery
- Computational Biology
- Molecular Modeling
- Drug-Target Interaction Prediction
- QSAR Modeling
- Virtual Screening
βοΈ MLOps & Infrastructure
- CI/CD for ML
- Model Deployment
- Performance Monitoring
- Scalable ML Systems
- Cloud Infrastructure (Azure, GCP)