Principal Machine Learning Engineer

Role Overview & Key Responsibilities

This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale.

You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels.

Responsibilities

• Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products.
• Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning.
• Define and own the multi-year ML roadmap for GenAI infrastructure — including agent frameworks, RAG systems, world-class evaluation loops, and integration with MCP, browser, and vision pipelines.
• Identify and integrate cutting-edge ML methods / research (deep learning, large models, recommender systems, LLMs, etc.) into Ema’s products or infrastructure.
• Research, prototype, and integrate cutting-edge ML and LLM advancements (reasoning, memory architectures, multi-modal perception, long-context models, autonomous agents) into the platform.
• Optimize trade-offs between accuracy, latency, cost, interpretability, and real-world reliability across the agent lifecycle — from prompt design to orchestration and execution.
• Champion engineering excellence — drive observability, reproducibility, versioning, testing, and bias-aware development across ML and agentic systems.
• Mentor and elevate senior engineers and researchers, fostering a culture of scientific rigor, experimentation, and system-level thinking.
• Collaborate cross-functionally with product, infra, and research teams to align ML innovation with enterprise needs — enabling secure integrations, privacy-aware deployments, and scalable use cases.
• Influence data strategy — guide how retrieval indices, embeddings, structured/unstructured corpora, and feedback loops evolve to improve grounding, factuality, and reasoning depth.
• Drive system scalability and performance — ensuring ML agents and RAG pipelines can operate across billions of knowledge objects, diverse APIs, and real-time enterprise contexts.

Required Skills & Qualifications

• Bachelor’s or Master’s (or PhD) degree in Computer Science, Machine Learning, Statistics, or a related field.
• A strong track record (usually 10-12+ years) of applied experience with ML techniques, especially in large-scale settings.
• Experience building production ML systems that operate at scale (latency / throughput / cost constraints).
• Experience in Knowledge retrieval and Search space.
• Exposure in building Agentic Systems and Frameworks.
• Proficiency in relevant programming languages (e.g. Python, C++, Java) and ML frameworks (TensorFlow, PyTorch, etc.).
• Strong understanding of the full ML lifecycle: data pipelines, feature engineering, model training, serving, monitoring, maintenance.
• Experience designing systems for monitoring, diagnostics, logging, model versioning, etc.
• Deep knowledge of computational trade-offs: distributed training, inference, optimizations (e.g. quantization, pruning, batching).
• Excellent communication skills; ability to present complex systems / trade-offs to technical and non-technical stakeholders.
• Experience mentoring senior engineers; ability to lead technical discussions and influence across orgs.

Why Join Ema?

• Work at the forefront of agentic AI systems—driving real enterprise transformation.
• Own mission-critical platforms that make or break Ema’s capabilities.
• Join an elite team of engineers, product thinkers, and AI researchers who value deep execution.
• Help define the architectural, cultural, and operational DNA of a company set to define a new category.

Our culture & Values

• High Bar on Quality – We value excellence and expect world-class execution.
• Ownership & Accountability – We take full responsibility for our work and outcomes.
• Impact-Driven Approach – We set ambitious goals and measure success through real-world impact.
• Team Collaboration & Growth – We believe in continuous learning, knowledge sharing, and supporting each other.
• No Hierarchy, Just Execution – Everyone is an individual contributor, focused on delivering results.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.