Machine Learning Engineer (W2 Only)

Job Title: Machine Learning Engineer Strictly- on w2. Location: Remote / Hybrid / Onsite (US) Job Summary: We are seeking an experienced Machine Learning Engineer to build, deploy, and scale machine learning solutions in cloud-native production environments. The ideal candidate will combine strong software engineering skills with expertise in MLOps, cloud technologies, and production-grade AI systems. Key Responsibilities: • Design, develop, and deploy machine learning models and AI applications into production environments. • Build scalable training, inference, and feature engineering pipelines. • Develop MLOps frameworks for model versioning, monitoring, retraining, and governance. • Collaborate with Data Scientists, Data Engineers, and Product teams to deliver end-to-end machine learning solutions. • Build APIs and microservices to expose machine learning models for enterprise applications. • Implement CI/CD pipelines for automated testing and deployment of ML solutions. • Monitor production systems for model drift, performance degradation, and operational issues. • Optimize models for latency, scalability, and cost efficiency. • Create technical documentation and architectural design artifacts. Required Skills: • Strong programming skills in Python, SQL, and software engineering principles. • Experience with TensorFlow, PyTorch, Scikit-learn, and XGBoost. • Hands-on experience with Docker, Kubernetes, and container orchestration. • Experience with AWS services such as SageMaker, Lambda, ECS, EKS, S3, and Redshift. • Experience with Azure Machine Learning or Databricks is a plus. • Strong understanding of CI/CD tools including Jenkins, GitHub Actions, and Azure DevOps. • Experience building REST APIs using FastAPI or Flask. • Familiarity with Spark, PySpark, and distributed computing frameworks. • Experience with MLflow, Kubeflow, Airflow, and model monitoring tools. Preferred Qualifications: • Experience with Large Language Models (LLMs), RAG architectures, prompt engineering, and AI agents. • Experience with LangChain, Hugging Face, OpenAI APIs, and Vector Databases such as Pinecone, FAISS, or ChromaDB. • Experience in highly regulated industries such as Banking, Healthcare, and Insurance. • Strong understanding of system design, scalability, and cloud architecture. • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field.