Join a forward-thinking engineering team focused on transforming AI research into real-world applications. In this role, you'll design and deploy intelligent systems that solve complex business challenges, leveraging the latest in generative AI and machine learning technologies.
What You’ll Do
- Design and implement AI-driven features that integrate seamlessly with existing software platforms, ensuring scalability and reliability.
- Collaborate closely with data scientists and engineers to identify optimal AI strategies and translate prototypes into robust production systems.
- Work hands-on with large language models and NLP systems, fine-tuning prompts and outputs to meet specific functional requirements.
- Apply best practices in security, monitoring, and model evaluation to maintain high standards across all AI deployments.
- Ensure responsible AI principles are embedded throughout the development lifecycle, from design to deployment.
- Develop custom metrics and testing frameworks to assess model accuracy, fairness, and alignment with business goals.
- Optimize data pipelines using vector databases and embedding techniques to support efficient retrieval and processing.
What We’re Looking For
- Proven experience building and deploying AI systems, particularly in NLP, LLMs, and statistical modeling.
- Strong command of Python and experience working with AI frameworks and cloud-based AI services such as AWS Bedrock, Azure AI, or Vertex AI.
- Deep understanding of generative model trade-offs and the ability to select and adapt the right tool for each use case.
- Experience developing server-side APIs and orchestrating AI workflows at scale.
- Ability to clearly explain technical AI concepts to both technical and non-technical audiences.
- Familiarity with testing methodologies for AI systems, including bias detection, performance benchmarking, and compliance checks.
- Skill in crafting and refining prompts to achieve desired behaviors in complex AI models.
- Experience deploying solutions on major cloud platforms with a focus on automation, monitoring, and maintainability.
