ML Engineer - AI-Powered Automation & Workflow Intelligence

Position Overview

A pioneering tech startup at the intersection of AI and intelligent automation is transforming how enterprises scale complex operations. Backed by global clients in high‐value sectors and an experienced founding team, the company is building a next‐generation platform to revolutionize human–machine collaboration. As one of the earliest technical hires, the ML Engineer will play a mission‐critical role in defining the architectural and engineering foundation of the product while working on cutting‐edge AI systems that have a deep impact on technology, the team, and the market. Location: Bay Area, CA (On-site). Employment Type: Full-Time. Level: Senior Individual Contributor. Industry: Artificial Intelligence, Enterprise Software, Workflow Automation.

Key Responsibilities

• Design and implement scalable, production-grade ML systems that serve as the intelligence layer of a flagship automation platform.
• Lead the full lifecycle of ML development, from data ingestion to deployment, including experimentation, training, evaluation, and monitoring.
• Develop innovative solutions involving large language models (LLMs), multimodal architectures (text, image, graph), and multilingual adaptation.
• Build robust infrastructure for ML experimentation, model management, and deployment (MLOps).
• Partner closely with product and engineering leaders to align machine learning solutions with high-value business challenges.
• Establish reproducibility and performance standards while integrating research advancements into a practical, production setting.
• Mentor incoming AI team members and contribute to shaping the engineering culture and technical vision.

Required Qualifications

• 8+ years in ML, Deep Learning, or Applied AI, ideally with experience taking models from prototype to production.
• Strong background in foundational ML concepts, deep learning frameworks (e.g., PyTorch, TensorFlow, JAX), and distributed training.
• Proven success working with LLMs, transformers, or comparable foundation models in applied contexts.
• Hands-on experience with data pipeline orchestration and ML tooling (e.g., Airflow, MLflow, SageMaker, Vertex AI).
• Proficiency in Python and experience developing scalable APIs or backend services in cloud environments.
• High ownership mindset with the agility and drive typical of startup environments.
• Advanced degree (MS or PhD) in Computer Science, Applied Mathematics, or a related field is preferred.

Preferred Qualifications

• Practical exposure to multimodal ML (e.g., combining NLP with vision or graph data).
• Familiarity with ontologies, taxonomies, or structured semantic modeling.
• Experience with multilingual NLP models or internationalization of AI systems.
• Background in high-growth startups or early-stage technical leadership.

Benefits & Perks

• Shape the core AI systems of a product with tangible, enterprise-scale impact.
• Join a small, high-caliber team solving sophisticated automation challenges.
• Own key technical decisions and help shape a culture of engineering excellence.
• Competitive compensation package with significant equity upside.
• Collaborate in-person in the Bay Area while building globally scalable tech.