Overview
In this role you will design, build, and operationalize AI/ML solutions for enterprise clients. You’ll translate real-world problems into scalable AI systems and deploy models in production with robust data pipelines and MLOps. You’ll work across business and technical teams to deliver end-to-end AI capabilities, from model customization to integration and monitoring. This role offers the chance to influence client outcomes at scale and contribute to innovative AI deployments.
Responsibilities
- Formulate real-world problems into scalable AI/ML solutions
- Develop and implement ML algorithms, models and scalable data pipelines for training and production with DevOps & MLOps
- Customize Deep Learning and Gen AI models for business use cases
- Engage in R&D of new AI and high-performance compute algorithms and simulations
- Work with large-scale datasets and apply data preprocessing for high-quality training input
- Implement and maintain efficient data storage and retrieval for models and knowledge
- Justify value of model approaches in business problems
- Collaborate with cross-functional teams to achieve end-to-end project goals and production integration
Key requirements
- Proven experience as a machine learning engineer or scientist deploying models in production at scale with monitoring, alerts, and auditing
- Strong grounding in computer science concepts and programming
- Experience with distributed computing systems and architectures (big data, HPC, cloud) and deploying AI/ML software to cloud environments
- Strong written and verbal communication
- Strong client-facing skills in a consulting environment
- Cross-functional collaboration
- Python and Python-based ML frameworks (TensorFlow, PyTorch)
- Experience with language model APIs and optimizing usage for specific applications
- Programming languages: Python, C++, Java, R, SQL
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