Building and improving AI-powered products by leveraging state-of-the-art generative AI, NLP, and machine learning models to directly impact user experience.
Requirements
- 5+ years of proven experience in AI/ML engineering, building production-grade AI systems, and applying machine learning models to solve real-world business problems.
- Hands-on experience implementing LLM-based generative AI systems using both commercial and open-source models (e.g., OpenAI, Anthropic, Meta).
- Demonstrated ability to optimize AI systems for latency, efficiency, and scalability.
- Strong expertise in NLP, machine learning models, prompt engineering, and generative AI applications.
- Experience building production-grade retrieval-augmented generation (RAG) systems using structured, unstructured, and graph data.
- Familiarity with AI/ML evaluation, training data collection, human labeling, and model validation.
- Experience designing, building, and supporting APIs for use by other engineering teams.
Responsibilities
- Designing, developing, and deploying AI systems
- Collaborate with product managers, engineers, designers, and AI leadership to rapidly prototype, iterate, and scale innovative solutions.
- Continuously improve existing AI systems using new models, tools, and prompt engineering techniques.
- Evaluate third-party AI solutions to guide build vs. buy decisions.
- Develop clear AI engineering specifications based on product requirements.
- Communicate technical decisions, progress, and results to peers and stakeholders.
- Make informed technical decisions in situations of uncertainty or ambiguity.
Other
- Master’s degree or PhD in Computer Science, AI/ML, Computational Linguistics, Data Science, Mathematics, or related fields.
- Thrives in a fast-paced, ambiguous environment
- Enjoys solving complex technical problems
- Passion for staying at the forefront of AI research and application.
- Excellent communication skills, able to explain sophisticated technical concepts to both technical and non-technical stakeholders.
