---
title: 'MLOps Team Lead at Fundamental'
canonical: 'https://feeny.ai/job/mlops-team-lead-fundamental-europe-mznfy9kpx57f'
type: 'job'
last_seen: '2026-09-16'
---

# MLOps Team Lead at Fundamental

- **Company:** Fundamental
- **Location:** Europe
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-07-01
- **Last confirmed live:** 2026-09-16
- **Apply:** https://jobs.ashbyhq.com/fundamental/48f0baea-855c-49a1-b442-5869cd125398

## Job description

## About Fundamental

Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.

At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.

## Key responsibilities

- Lead and mentor a team of MLOps engineers, fostering technical growth and a culture of operational excellence
- Define and drive the MLOps roadmap, aligning infrastructure capabilities with Research, Engineering and product objectives
- Establish best practices, standards, and processes for ML infrastructure, deployment, and operations
- Own technical decision-making for ML infrastructure architecture and tooling choices
- Architect and oversee scalable, automated machine learning pipelines, CI/CD workflows, and orchestration frameworks
- Drive the design and implementation of robust model serving infrastructure using platforms like Triton, TorchServe, TensorFlow Serving, and KServe
- Define inference architecture strategy optimized for ultra-low latency and high throughput
- Design and maintain feature stores, robust data pipelines, and scalable storage solutions to efficiently handle large volumes of data
- Collaborate with research teams to bridge the gap between experimentation and production
- Define logging, alerting, and monitoring strategy to track model performance, drift, and system reliability

Must have

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
- 7+ years of experience in MLOps, with 5+ years in a technical leadership role
- Strong software engineering skills in Python, with experience in Bash and/or Go
- Proven track record of building and leading high-performing MLOps or infrastructure teams
- Experience building and designing MLOps infrastructure from the ground up
- Deep experience with MLOps platforms (MLflow, WandB, etc.) and frameworks (PyTorch, TensorFlow, etc.)
- Deep experience with model serving frameworks (Triton, TorchServe, TensorFlow Serving, KServe) for high scalability and low latency inference
- Experience building and managing data pipelines to support both model training and inference
- Good experience with Kubernetes on a major cloud provider (AWS, GCP, or Azure) and with infrastructure as code (Terraform, Helm, GitOps)
- Proficient with observability and monitoring tools (Prometheus, Grafana, Datadog, OpenTelemetry)
- Excellent communication skills with ability to translate between research and production contexts

## Nice to have

- Experience with workflow orchestration tools (Kubeflow, Airflow, Argo Workflows)
- Experience with FastAPI and backend applications
- Familiarity with data platforms like Databricks or Snowflake
- Experience with LLM/foundation model serving and optimization
- Exposure to SRE practices or cloud security certifications
- Experience scaling ML infrastructure for AI startups

## Benefits

- Competitive compensation with salary and equity
- Comprehensive health coverage for you and your dependents
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
- Relocation support for employees moving to join the team in one of our office locations
- A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

## About Fundamental

## Company Overview
- **One-liner**: Fundamental builds foundation models purpose‑designed for tabular data, enabling enterprises and governments to make accurate predictions and confident decisions.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Jeremy Fraenkel (CEO), Gabriel Suissa (Co‑Founder); built by DeepMind alumni

## Core Business
- Primary industry: Artificial intelligence / Enterprise AI (Large Tabular Models)
- Target customers: Large enterprises and government agencies (Fortune 100 clients)
- Mission: “To create a world of abundance by giving humanity the Power to Predict.”

## Products & Services
- **[NEXUS – Large Tabular Model (LTM)]**: A deterministic foundation model pre‑trained on billions of tables to ingest structured data (rows/columns) and capture complex, non‑linear feature interactions. Deployable with one line of code, integrates deeply with AWS, and designed for enterprise‑grade privacy and security. Unlike LLMs, NEXUS can reason over extremely large datasets (billions of rows) and provides consistent answers every time.

## Market Standing
- **Valuation/Market Cap**: $1.4 billion post‑money (as of February 2026)
- **Key Metric**: Total funding raised – $255 million (Series A: $225M led by Oak HC/FT, Valor Equity Partners, Battery Ventures, Salesforce Ventures; Angel round: $30M from investors including Perplexity CEO Aravind Srinivas, Brex co‑founder Henrique Dubugras, Datadog CEO Olivier Pomel)
- **Notable Investors/Partners**: Oak HC/FT, Valor Equity Partners, Battery Ventures, Salesforce Ventures, Hetz Ventures; strategic partnership with Amazon Web Services (AWS)
- **Growth Signals**: Emerged from stealth in February 2026 with seven‑figure contracts from Fortune 100 clients; headcount grew from founding to 46 employees with +28% monthly growth; operates globally (San Francisco, Barcelona, Israel, UK, etc.)

## Competitive Advantages
- **Deterministic & scalable**: Unlike transformer‑based LLMs, NEXUS is deterministic and can analyze tables with billions of rows without context‑window limitations.
- **Purpose‑built for tabular data**: Captures non‑linear feature interactions that LLMs miss, unlocking trillions of dollars in value from structured data.
- **Research‑led with academic rigor**: Team includes DeepMind alumni; model built on a non‑transformer architecture designed specifically for real‑world tabular data.
- **One model, many use cases**: Replaces armies of data scientists with a single foundation model that works across industries (finance, healthcare, energy, etc.).

## Strategic Focus
- **Expansion**: Deepening the AWS integration and scaling NEXUS across more Fortune 500/global government clients.
- **Talent acquisition**: Hiring across research (Barcelona), engineering (Europe, SF), and commercial roles (SF, Houston) to accelerate model development and go‑to‑market.
- **Category creation**: Pioneering the “Large Tabular Model” (LTM) category to differentiate from LLM companies and establish leadership in predictive AI for structured data.

## Why Work Here
- **Solve hard problems**: Work on groundbreaking research and engineering for a new modality of AI (tabular data) that most labs ignore.
- **Exceptional team**: Collaborate with DeepMind alumni and top researchers from Cohere, AI21 Labs, Google DeepMind, Mistral AI, and others.
- **Global and flexible**: Hubs in San Francisco (HQ), Barcelona (research), and remote‑friendly roles across Europe and the US.
- **Rapid growth**: Joining a well‑funded, high‑valuation startup at Series A stage with real revenue and Fortune 100 customers—clear trajectory.
- **Mission‑driven**: “Power to Predict” aims to transform decision‑making in enterprises and governments, offering tangible societal impact.
- **Culture**: Described as rigorous, ambitious, and supportive of deep research and patient engineering.

## Sources
1. [fundamental.tech](https://fundamental.tech/)
2. [fundamental.tech/company](https://fundamental.tech/company)
3. [fundamental.tech/careers](https://fundamental.tech/careers)
4. [TechCrunch - Funding announcement](https://techcrunch.com/2026/02/05/fundamental-raises-255-million-series-a-with-a-new-take-on-big-data-analysis/)
5. [LinkedIn Company Page](https://www.linkedin.com/company/fundamentalhq)

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