Key Responsibilities
Architect & Deploy ML/DL Systems
Design and implement scalable ML pipelines: preprocessing, feature engineering, model training, evaluation, deployment.
Engineer low-latency, high-throughput inference systems suitable for enterprise use cases.
Domain-Centric Solutioning
Healthcare AI: Architect HIPAA/FHIR-compliant workflows for EMR/EHR, clinical notes, imaging, and life sciences data.
Salesforce AI: Build and integrate AI systems with Einstein 1 Platform, Apex, SOQL, Agentforce, Data Cloud, and MuleSoft APIs.
Model Optimization & Performance

o Apply advanced ML/DL techniques: CNNs, RNNs, transformers, ensemble methods. o Optimize models for speed, cost, and accuracy via quantization, distillation, pruning, and distributed training.
Infrastructure & MLOps o Build robust ML pipelines with CI/CD, Kubernetes, Docker, MLflow/Kubeflow, and Airflow.

o Deploy across AWS (SageMaker, Bedrock), Azure AI, or GCP Vertex AI with observability, telemetry, and drift detection. o Implement scalable, compliant architectures meeting HIPAA/GDPR standards.
Future Growth into Generative AI (optional but encouraged)

o Explore LLMs, RAG, fine-tuning (LoRA, QLoRA, PEFT) and orchestration frameworks (LangChain, LlamaIndex).

o Experiment with vector databases (Pinecone, FAISS, Milvus, Weaviate)



and hybrid retrieval pipelines.
Leadership & Mentorship o Write clean, production-grade Python (PyTorch, TensorFlow, Keras).

o Mentor engineers/data scientists, enforce coding & architectural best practices.

o Translate complex business challenges into scalable AI solutions.

What You Bring
Experience: 48+ years in AI/ML/DL engineering or architecture, with proven success delivering production-grade systems.
Core Technical Skills:

o Expert Python with PyTorch, TensorFlow, Keras.

o Robust knowledge of ML algorithms, DL architectures (transformers, attention models, CNNs, RNNs).

o Data pipelines, embeddings, ETL/ELT, real-time streaming.
Infrastructure:

o Cloud platforms (AWS, Azure, GCP).

o CI/CD, Kubernetes, Docker, MLOps pipelines (MLflow, Kubeflow, Airflow).
Domain Expertise (must have one, ideally both):

o Healthcare: HIPAA/FHIR/HL7, EMR/EHR, clinical data, imaging.

o Salesforce: Einstein 1 Platform, Agentforce, Apex/Lightning, SOQL, Data Cloud, MuleSoft.
Nice-to-Have (Future Growth): Exposure to Generative AI/LLMs and orchestration frameworks.
Soft Skills: Systems-level thinker, problem solver, solid communicator, team-oriented leader.

📌 Ai/ml Architect Coimbatore (India)
🏢 hiringhood
📍 India