Machine Learning Engineer

Machine Learning Engineer (Mid–Senior Level) Location: Remote (United States) Employment Type: Full-Time Experience: 5+ Years Compensation: Competitive Salary + Comprehensive Benefits About the Role: We are seeking a talented Machine Learning Engineer to join our growing AI team. In this role, you'll design, build, deploy, and optimize machine learning models that power intelligent products and data-driven decision-making. You'll collaborate closely with Data Scientists, Software Engineers, Product Managers, and MLOps Engineers to transform research into scalable production systems while improving model performance, reliability, and efficiency. If you're passionate about artificial intelligence, large-scale data processing, and deploying real-world ML solutions, we'd love to hear from you. Responsibilities: Design, develop, train, and deploy production-grade machine learning models. Build scalable ML pipelines for data preprocessing, feature engineering, training, validation, and deployment. Develop predictive models using supervised, unsupervised, and deep learning techniques. Optimize model accuracy, latency, scalability, and reliability. Collaborate with software engineering teams to integrate ML solutions into production applications. Monitor model performance and implement retraining strategies. Perform feature engineering and data analysis on structured and unstructured datasets. Work with cloud-based ML platforms and distributed computing frameworks. Develop APIs and services for model inference. Implement MLOps best practices including CI/CD, model versioning, and automated deployment. Stay current with emerging AI and machine learning technologies. Document technical solutions and mentor junior engineers when needed. Required Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, Statistics, or a related field. 5+ years of professional experience in Machine Learning Engineering or AI development. Strong programming experience in Python. Experience developing and deploying machine learning models in production. Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts. Experience with large datasets and feature engineering. Knowledge of model evaluation, optimization, and hyperparameter tuning. Experience building REST APIs for ML services. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Preferred Qualifications: Experience with Large Language Models (LLMs) and Generative AI. Experience working with Retrieval-Augmented Generation (RAG). Experience fine-tuning transformer models. Knowledge of Vector Databases. Experience deploying AI solutions on cloud platforms. Familiarity with Kubernetes and containerized ML deployments. Experience with real-time inference systems. Contributions to open-source AI or machine learning projects. Technical Skills: Programming Python SQL Java (Preferred) Scala (Preferred) Machine Learning Scikit-learn TensorFlow PyTorch XGBoost LightGBM CatBoost Deep Learning CNN RNN LSTM Transformers BERT GPT Models Generative AI OpenAI APIs LangChain LlamaIndex Hugging Face RAG Prompt Engineering Data Engineering Pandas NumPy Spark Hadoop Airflow MLOps MLflow Kubeflow Docker Kubernetes GitHub Actions Jenkins CI/CD Pipelines Cloud Platforms AWS SageMaker Azure Machine Learning Google Vertex AI Databases PostgreSQL MySQL MongoDB Redis Pinecone Weaviate FAISS Visualization Tableau Power BI Matplotlib Plotly Ideal Candidate: We're looking for someone who: Has strong experience building production-ready machine learning systems. Enjoys solving complex AI and data engineering challenges. Understands software engineering best practices alongside machine learning. Is passionate about Generative AI and emerging technologies. Can communicate technical concepts effectively with cross-functional teams. Takes ownership from model development through production deployment. Show more Show less