We are seeking a results-driven Senior Machine Learning Engineer with 5+ years of experience to join our AI/ML team. The ideal candidate will have a strong background in building and deploying ML models, hands-on product development experience, and a solid grasp of ML Ops practices. Leadership capabilities and a portfolio of past work are highly valued.

Key Responsibilities:

• Design, develop, and implement machine learning models and algorithms tailored to real-world business problems.
• Optimize and scale ML solutions for deployment in production environments.
• Collaborate closely with data scientists, software engineers, and stakeholders to integrate ML models into existing systems and products.
• Conduct experiments, perform hyperparameter tuning, and evaluate models to improve performance.
• Monitor, maintain, and retrain production models to ensure reliability, efficiency, and scalability.
• Drive best practices in ML Ops, including versioning, CI/CD, testing, and automated model monitoring.
• Lead or mentor junior team members and contribute to overall AI/ML strategy.

Required Qualifications:

• 5+ years of experience in machine learning engineering or a related field.
• Proven experience developing and deploying ML-powered products; having a demo or portfolio is a plus.
• Proficiency in programming languages such as Python (preferred), R, or Java.
• Strong understanding of ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
• Working knowledge of cloud ML platforms such as AWS SageMaker, GCP AI Platform, or Azure ML.
• Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
• Experience with data processing and big data technologies like Hadoop and Spark.
• Strong understanding of MLOps tools and practices for monitoring, deployment, and lifecycle management.

Preferred Skills:

• Experience with deep learning architectures including CNNs, RNNs, and GANs.
• Knowledge of natural language processing (NLP) or computer vision.
• Experience with Docker, Kubernetes, or other containerization and orchestration tools.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
• Demonstrated leadership experience or project ownership in past roles.