Machine Learning Engineer | Building Agentic AI & Scalable ML Systems
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Turning code into cognition. From model weights to agentic intelligence — I build systems that learn, adapt, and deploy at scale.
class MachineLearningEngineer:
def __init__(self):
self.name = "Shinde Aditya"
self.focus = [
"LLMs", "Agentic AI", "Deep Learning", "ML Pipelines", "MLOps"
]
self.code = [
"Python", "PyTorch", "TensorFlow", "JAX", "Scikit-learn",
"NumPy", "Pandas", "Matplotlib", "Seaborn"
]
self.mlops = [
"MLflow", "Weights & Biases", "DVC", "Docker", "Kubernetes"
]
self.agentic_ai = [
"LangChain", "LlamaIndex", "Transformers", "RAG Pipelines", "OpenAI API", "Vector DBs"
]
self.deployment = [
"FastAPI", "Flask", "Streamlit", "Gradio", "AWS SageMaker", "GCP AI Platform"
]
self.tools = [
"Jupyter", "VS Code", "Git", "GitHub", "Conda", "Poetry"
]
self.communication = [
"Slack", "Zoom", "Notion", "LinkedIn", "GitHub Projects"
]
def build(self):
return "From prototype to production — AI that performs, learns, and scales."
aditya = MachineLearningEngineer()
print(aditya.build())
