We are seeking a Engineer with end-to-end expertise in designing, developing, deploying, and maintaining machine learning solutions. This role requires a hands-on engineer who can work across data engineering, model development,
MLOps, and API integration to build scalable AI-driven applications. Location – Remote
Key Responsibilities:• Data Engineering & Processing:• Design and implement scalable
ETL/ELT
pipelines for structured and unstructured data.• Clean, normalize, and preprocess data for ML models.• Work with Graph Databases (Neo4j, AWS Neptune) and Vector Databases (Weaviate, Pinecone, FAISS).
• Model Development & Fine-Tuning:• Train and fine-tune LLMs and deep learning models using Hugging Face,
PyTorch, TensorFlow.• Implement retrieval-augmented generation (RAG) for knowledge-based AI.• Optimize model performance for efficiency and scalability.• MLOps & Model Deployment:• Develop CI/CD pipelines for ML model training and deployment using MLflow, Kubeflow, SageMaker.• Deploy models as APIs using FastAPI, Flask, or gRPC.• Automate model monitoring, drift detection, and retraining.• Application & API Development:• Build APIs and microservices for AI applications.• Integrate ML models with LangChain for AI-powered applications.• Implement scalable solutions in AWS, GCP, or Azure.• Performance Optimization & Security:• Optimize model inference speed and reduce cloud costs.• Ensure data security and compliance (HIPAA, GDPR where applicable).Required Skills:• Machine Learning & AI:• Strong background in ML, deep learning, LLMs, NLP.• Experience with Transformer models (BERT, GPT, T5, LLaMA, etc.).• Programming & Development:• Proficiency in Python (PyTorch, TensorFlow, Scikit-Learn).• Strong experience in APIs and microservices (FastAPI, Flask, gRPC).• Data & Infrastructure:• Experience with Graph Databases (Neo4j, AWS Neptune).• Knowledge of Vector Databases (Weaviate, Pinecone, FAISS).• Familiarity with Snowflake, PostgreSQL, NoSQL databases.• MLOps & Cloud:• Experience with MLflow, Kubeflow, SageMaker for model lifecycle management.• Proficiency in Docker, Kubernetes, Terraform.• Strong understanding of AWS/GCP/Azure services.• AI Application Development:• Experience integrating AI models with LangChain for intelligent applications.• Understanding of retrieval-augmented generation (RAG) workflows.
