7 months ago
Responsibilities
- Lead the technical direction of GenAI and agentic ML systems for enterprise AI agents.
- Architect and implement scalable production pipelines for model training and evaluation.
- Define and own the multi-year ML roadmap for GenAI infrastructure.
- Integrate cutting-edge ML methods into Ema’s products or infrastructure.
- Research and prototype advancements in ML and LLM technologies.
- Optimize trade-offs between accuracy, latency, and cost across the agent lifecycle.
- Champion engineering excellence in observability and reproducibility.
- Mentor senior engineers and foster a culture of scientific rigor.
- Collaborate with cross-functional teams to align ML innovation with enterprise needs.
- Influence data strategy to improve grounding and reasoning depth.
- Drive system scalability and performance across diverse APIs and contexts.
Requirements
- Bachelor’s or Master’s (or PhD) degree in Computer Science, Machine Learning, or related field.
- 10-12+ years of applied experience with ML techniques in large-scale settings.
- Experience building production ML systems that operate at scale.
- Knowledge in Knowledge retrieval and Search space.
- Exposure to building Agentic Systems and Frameworks.
- Proficiency in programming languages like Python, C++, or Java.
- Strong understanding of the full ML lifecycle and system monitoring.
- Deep knowledge of computational trade-offs in ML.
- Excellent communication skills for presenting complex systems.
- Experience mentoring senior engineers and leading technical discussions.
Benefits
- Work at the forefront of agentic AI systems.
- Own mission-critical platforms that impact Ema’s capabilities.
- Join an elite team of engineers and AI researchers.
- Help define the architectural and operational DNA of a pioneering company.