Principal AI/ML Architect at TensorOps

Role overview

Qualifications

8+ years of professional experience in machine learning and software engineering
Significant client-facing experience
Proven leadership and project management experience
Deep expertise in Python and its data science ecosystem

Responsibilities

Lead Technical Strategy & Architecture for client projects
Manage Client Engagements as the primary technical point of contact
Lead & Mentor Engineering Teams for project delivery
Drive Innovation in architecting and implementing complex ML systems

Key facts

Remote from: Portugal
Full time
Senior (5-10 years)
English

Hard skills

Python (Programming Language) Machine Learning FastAPI TensorFlow LightGBM MLflow Kubeflow Amazon Web Services gRPC Recommender Systems Client Services Project Management

Other skills

Leadership
Mentorship

About the company

TensorOps

TensorOps is a leading provider of machine learning (ML) and artificial intelligence (AI) services for startups and companies. The company specializes in two key areas: Search Relevance and TimeSeries. Search Relevance: TensorOps helps companies improve their search algorithms to deliver more relevant results to their customers. This involves analyzing search queries, optimizing ranking algorithms, and developing custom solutions to improve search relevance. By improving search relevance, companies can increase customer engagement, retention, and ultimately revenue. TimeSeries: TensorOps provides expertise in TimeSeries forecasting, which is a technique used to predict future values based on historical data. This is particularly useful for companies that deal with time-sensitive data, such as financial data, healthcare data, and manufacturing data. TensorOps works with companies to develop custom forecasting models that can help them make more accurate predictions, improve planning, and optimize resource allocation. TensorOps is known for its high level of expertise, customer service, and attention to detail. The company works closely with clients to understand their needs and develop tailored solutions that deliver tangible business results. Whether it's improving search relevance, optimizing forecasting models, or developing custom ML and AI solutions, TensorOps is committed to helping its clients succeed in today's fast-paced business environment.

Company details

Company size2 - 10

Links

Website LinkedIn See all jobs

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

Principal ML Architect (Client-Facing, Agentic AI) - Portugal

Location: Portugal (Fully Remote)

Build the Next Generation of AI Products with TensorOps

TensorOps is an applied-machine-learning studio that helps organisations across Europe and North America design, train, and deploy production-grade GenAI systems. Our team blends research depth with pragmatic engineering, and we’re looking for a seasoned architect to lead our client engagements and technical teams in Portugal.

What We’re Working On

Conversational Copilots: Intelligent assistants that augment and empower knowledge workers.
Autonomous Agentic Systems: Sophisticated agents that perform complex research, analysis, and actions for market-leading platforms.
High-Performance Search & Recommendation: Building large-scale, low-latency recommender systems, ad-tech platforms, and search solutions.
Decision-Support Tools: High-stakes systems for critical applications in healthcare, finance, and e-commerce.

Core Stack

Python, FastAPI, Docker
TensorFlow, LightGBM, CatBoost
Open-source & Commercial LLMs
LangChain / LangGraph, Langfuse, LlamaIndex
MLFlow, Kubeflow
AWS and GCP

The Role

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.

You will:

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.

About You

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.

Why TensorOps?

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.