Description

You will lead the design, development, and deployment of end-to-end AI/ML solutions from prototype through to production.

This role is remote.

Responsibilities

• Implement machine learning models for classification, regression, NLP, time-series, and generative AI.
• Build scalable data pipelines and feature stores for training and inference.
• Develop APIs and microservices to support real-time and batch model inference.
• Optimize model performance, latency, reliability, and operational cost.
• Apply MLOps best practices including CI/CD, model versioning, monitoring, and retraining.

Required Skills

• 5+ years of experience in machine learning or AI engineering.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
• Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud platforms, specifically AWS, Azure, or GCP.
• Experience deploying models using Docker or Kubernetes.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Familiarity with SQL and large-scale data processing.
• Experience with MLflow, SageMaker, Vertex AI, or Azure ML.

Key Skills

Education

Bachelor's or Master's degrees