Why this role stands out
You will thrive in this hybrid role, leveraging your expertise in AI/ML to design and deploy cutting-edge predictive analytics and generative AI solutions, contributing to a growing organization's impactful work. This position offers significant opportunities for skills development across the full AI lifecycle and collaboration with a talented team.
Quick overview
Job description
In this role, you will contribute to the development of production-grade machine learning and AI applications, including predictive models, agentic AI systems, retrieval-augmented generation (RAG) solutions, and large language model (LLM) integrations. You will work across the full AI lifecycle, from system design and model development through deployment, monitoring, and optimization, while helping establish best practices for modern AI engineering.
Required Skills & Experience
- 7+ years of experience designing, developing, and deploying machine learning solutions in production environments
- Python development experience, including building reusable packages, frameworks, and automation tools
- Databricks for large-scale data processing, analytics, and machine learning workflows
- Deep understanding of machine learning systems design, MLOps, model lifecycle management, and scalable inference
- Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform
- Hands-on experience with containerization technologies and CI/CD pipelines
- Master's degree in Computer Science, Data Science, Software Engineering, or a related field
What You Will Be Doing
- Design, develop, and deploy scalable AI and machine learning applications
- Build reusable Python libraries, machine learning frameworks, and data processing pipelines
- Develop solutions utilizing LLMs, retrieval-augmented generation (RAG), and agent-based architectures
- Create evaluation, monitoring, and governance frameworks for AI systems
- Optimize databases, data pipelines, and model performance for large-scale workloads
- Research and implement emerging AI and machine learning technologies to drive innovation
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