Principal AI/ML Architect

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Principal ML Architect leading AI/ML initiatives at TensorOps. Overseeing technical strategy and mentoring teams for complex client projects.

Posted 7/13/2026full-timeRemote • 🇵🇹 PortugalLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and delivering large-scale AI/ML systems, with a strong focus on client engagement and technical leadership. Proficient in guiding engineering teams and managing complex software projects from inception to deployment.

Highest-signal resume keywords

Machine Learning ArchitectureClient Engagement ManagementPython ProgrammingLarge Language Models (LLMs)MLOps and Cloud Infrastructure

ATS Keywords

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Hard Skills

Machine LearningSoftware EngineeringArchitecting AI SystemsData Science EcosystemAgentic Design PatternsLearning to Rank (LTR)Recommender AlgorithmsRAG PipelinesScalability DesignProject Management

Soft Skills

LeadershipMentoringClient AdvisoryTechnical CommunicationTeam Collaboration

Tools & Technologies

PythonPandasNumPyScikit-learnAWSGCP

Certifications & Qualifications

BSc in Computer ScienceMS in EngineeringPhD in Related Field

Industry Keywords

AI SystemsAgent-Based ModelingMulti-Agent SystemsProduction-Grade SolutionsTechnical Delivery

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformNumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

As a Principal ML Architect, you will be the senior technical leader for our most ambitious client projects. You will act as a trusted advisor to clients, a mentor to your engineering team, and the chief architect for complex AI systems. This is a hands-on leadership role that combines deep technical expertise with strategic client management.
Lead Technical Strategy & Architecture: Partner with clients to understand their core business challenges and design sophisticated, scalable solutions leveraging machine learning, search, and agentic AI paradigms.
Manage Client Engagements: Serve as the primary technical point of contact for client stakeholders, translating complex concepts, managing expectations, and ensuring project success from a technical and business perspective.
Lead & Mentor Engineering Teams: Guide a team of talented ML engineers, fostering a culture of excellence, providing technical direction, and taking ultimate responsibility for project delivery.
Drive Innovation: Move beyond conventional ML to architect and implement cutting-edge agentic workflows, agent-based modeling, multi-agent systems, and complex RAG pipelines that deliver transformative value.
Oversee the Full Project Lifecycle: Steer projects from initial discovery and architectural design through to deployment, monitoring, and iteration, ensuring solutions are robust, efficient, and production-ready.

Requirements

What you’ll need

8+ years of professional experience in machine learning and software engineering, with a proven track record of architecting and delivering large-scale, production-grade AI/ML systems.
Significant client-facing experience is essential. You are comfortable and effective in a consulting or architectural role, capable of leading technical discussions with C-level executives and engineering teams alike.
Proven leadership and project management experience. You have successfully led engineering teams and managed the technical delivery of complex software projects.
Deep expertise in Python and its data science ecosystem (e.g., Pandas, NumPy, Scikit-learn).
Expert-level understanding of modern AI systems. You have deep, practical experience with Large Language Models (LLMs), agentic design patterns (e.g., LangChain/LangGraph), and classical ML at scale. You can speak with authority on topics like Learning to Rank (LTR), recommender algorithms, RAG, and fine-tuning.
Strong architectural foundation in software engineering, MLOps, and cloud infrastructure (AWS/GCP). You know how to design for scalability, reliability, and low-latency.
A BSc/MS/PhD in Computer Science, Engineering, or a related field, or equivalent practical experience that demonstrates your deep expertise.

Benefits

Comp & perks

Strategic Impact: Define the technical vision for high-stakes, real-world problems for industry-leading clients. Your work will directly shape client success and our company's reputation.
Lead Expert Teams: Guide and collaborate with a team of experienced ML engineers and researchers. Shape our engineering culture and mentor the next generation of talent.
Shape Our Future: As a senior leader, you will play a critical role in the direction of our technical offerings and growth. We offer competitive compensation and a clear path for professional and personal development.