Machine Learning Engineer – ML/AI, Python, LLM

Experience: 4+ Years
Job Type: Contract

We are seeking a Machine Learning Engineer with strong hands-on experience building, evaluating, and deploying ML/AI solutions in production. The ideal candidate will have expertise in classical ML, NLP/LLMs, model evaluation, and ML pipeline development, with strong data engineering capabilities.

Key Responsibilities

• Build, train, tune, evaluate, and deploy machine learning models for classification, regression, anomaly detection, and clustering.
• Work with XGBoost, LightGBM, CatBoost, Random Forest, Logistic Regression, Isolation Forest, K-Means, and other ML algorithms.
• Develop NLP solutions using BERT/DistilBERT, NER, sentence-transformers, embeddings, and semantic similarity.
• Build and integrate LLM-based applications using Gemini, GPT, Claude, or Llama.
• Design RAG pipelines, multi-agent workflows, structured JSON generation, confidence scoring, and hallucination detection.
• Develop configurable AI/business rule engines and runtime rule evaluation workflows.
• Build offline evaluation frameworks, model comparisons, A/B testing, human evaluation loops, and model quality monitoring.
• Deploy ML models as FastAPI/Flask REST services and develop batch inference pipelines with scheduling, status tracking, and failure recovery.
• Manage model versioning, experiment tracking, production rollout, and rollback strategies.
• Develop scalable data pipelines using Python, SQL, PostgreSQL, and Oracle to support ML workflows.
• Collaborate with backend teams using Java/Spring Boot, JPA/Hibernate, and microservices.
• Build dashboards and operational reporting using MicroStrategy.

Required Skills

• 4+ years of Machine Learning / Data Engineering experience.
• Strong Python, SQL, pandas, scikit-learn, and SQLAlchemy experience.
• Hands-on experience with classification, regression, clustering, anomaly detection, and ensemble models.
• Experience with NLP, transformers, embeddings, semantic similarity, or LLM applications.
• Production experience with Gemini / Vertex AI or comparable enterprise LLM platforms.
• Experience with ML model evaluation, validation, deployment, and monitoring.
• Strong understanding of ML pipelines and batch/online inference architectures.
• Experience with PostgreSQL and/or Oracle in data-intensive applications.

Nice to Have

• PyTorch or TensorFlow experience.
• pgvector, Pinecone, Chroma, or other vector databases.
• GKE/Kubernetes and CI/CD experience.
• Java/Spring Boot backend development.
• MicroStrategy experience.
• Healthcare, specialty pharmacy, EHR, claims, or prior authorization domain experience.