Mlflow Engineer

Job Title: MLflow Engineer
Location: Remote (USA)
Job Type: Full-Time
Experience Required: 5 7 Years
Priority: Urgent Hiring

We are seeking an experienced AI & Machine Learning Engineer with a strong background in Data Science to join our growing team. The ideal candidate will have hands-on experience designing, developing, and deploying machine learning and AI solutions that solve complex business problems. This is a full-time remote opportunity for professionals passionate about artificial intelligence, predictive analytics, and scalable ML systems.

• Design, develop, and deploy Machine Learning and AI models for production environments.
• Build predictive models, recommendation systems, classification, regression, clustering, and NLP solutions.
• Analyze structured and unstructured data to generate actionable business insights.
• Develop scalable data pipelines and feature engineering workflows.
• Work with large datasets using SQL, Python, and distributed computing frameworks.
• Train, evaluate, fine-tune, and optimize ML models for performance and scalability.
• Collaborate with Data Engineers, Software Engineers, Product Managers, and stakeholders to deliver AI-driven solutions.
• Implement MLOps best practices for model deployment, monitoring, and version control.
• Stay current with advancements in AI, Generative AI, LLMs, and machine learning technologies.

• 5 7 years of experience in AI, Machine Learning, and Data Science.
• Strong programming skills in Python.
• Experience with TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, or similar ML frameworks.
• Strong understanding of supervised and unsupervised learning algorithms.
• Experience with feature engineering, model evaluation, and hyperparameter tuning.
• Strong knowledge of statistics, probability, and predictive analytics.
• Experience with SQL and relational databases.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with Docker, Kubernetes, Git, and CI/CD pipelines.
• Knowledge of MLOps tools such as MLflow, Kubeflow, or SageMaker is a plus.

• Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or AI agents.
• Experience with NLP, Computer Vision, or Deep Learning projects.
• Familiarity with Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate).
• Exposure to Spark, Hadoop, or Databricks.
• Excellent analytical, problem-solving, and communication skills.

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.

For applications and inquiries,