Responsibilities
- Automate deployment, monitoring, and scaling of AI/ML models in cloud environments (primarily Azure).
- Maintain and troubleshoot production AI platforms, including break/fix support.
- Build and manage CI/CD pipelines that handle data, code, and model updates.
- Monitor model performance, drift detection, and implement updates or retraining as needed.
- Collaborate with cross-functional teams (data scientists, engineers, DevOps) to integrate AI into workflows.
- Support use cases such as natural language processing, sentiment analysis, recommendation systems, chatbots, and image-related tasks.
- Develop synthetic data pipelines and leverage production signals for ongoing model refinement.
- Potentially create prototypes or fine-tuned models to demonstrate enhancements.
- Ensure security, compliance, and reliability of ML systems.
- Provide occasional 24/7 support as part of a team rotation.
Basic qualifications
- Minimum 5+ years of hands-on software development experience (7+ preferred).
- Bachelor’s degree in Computer Science, Information Systems, or equivalent practical experience.
- Strong proficiency in Python for prototyping, scripting, and deployment.
- Solid experience with Azure cloud platform (additional AWS exposure a plus).
- Hands-on experience with containerization (Docker, Kubernetes) and orchestration.
- Familiarity with ML frameworks, libraries, and deployment practices (MLOps tools).
- Understanding of NLP, generative AI, and production ML challenges.
- Excellent communication skills to explain technical concepts to diverse audiences.
- Self-motivated, collaborative, and enthusiastic about real-world AI applications.
- Experience with fine-tuning or adapting large language models.
- Additional programming (e.g., Java or similar).
- Knowledge of reinforcement learning or advanced ML techniques.
Benefits
- Dental insurance
- Health insurance
- Vision insurance
Tags & focus areas
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