AI Engineer

Company Description

NestAI is a European physical AI lab building adaptive intelligence for unmanned systems, with a focus on defence and critical infrastructure. We develop mission-ready AI for real-world environments where reliability is non-negotiable.

At the core of what we build is an open, modular, and interoperable AI command foundation that integrates data from multiple sources — from UAV sensors and edge devices to situational intelligence platforms — and turns it into decision support and operational capability.

Rooted in Nordic engineering heritage, we focus on openness, reliability, and systems that earn trust through performance. We work with intent, iterate fast, and build technology that protects what matters most.

Role Description

We are looking for an AI Engineer to join NestAI. In this role, you will work at the intersection of advanced machine learning and real-world execution, designing the core logic, intelligent workflows, and decision-making frameworks that power our technology.

You will bridge the gap between cutting-edge AI research and high-performance, production-grade applications—whether deployed on the deep edge or scaled across cloud platforms.

In this position, we have two primary paths depending on your strengths and career interests: Internal Product R&D and Forward Deployed Engineering (FDE).

Internal Product R&D: You will focus on building, scaling, and maintaining the core infrastructure and cloud-based applications that power our long-term product vision. In this path, you will collaborate with our multidisciplinary teams—including embedded, cloud, and hardware engineers—to turn abstract models into real, high-performance systems.

You will be responsible for developing algorithms, training and optimizing models, building scalable data pipelines, and integrating AI solutions into core production environments.

Forward Deployed Engineering (FDE): Embedded directly in our customer's development environment, FDE squads shorten the path from development to fielded capability, validating product capability where assumptions are tested against operational reality.

This path is dynamic and highly impactful, where you will navigate shifting environments, collaborate with external stakeholders, and solve complex engineering challenges where adaptability is key.

Day-to-day

Responsibilities

• Intelligent Logic & Control: Designing and implementing algorithms for sequential decision-making, autonomous behavior, or specialized application workflows (ranging from LLM-driven applications to control systems).
• Model Optimization & Training: Developing custom training routines, fine-tuning foundation models, and optimizing loss functions to improve model robustness across diverse environments.
• Architecture & Performance: Collaborating with platform and embedded teams to optimize AI models for high-performance execution, whether deployed as scalable cloud services or low-latency policies on edge hardware (e.g., NVIDIA Jetson).
• Simulation & Validation: Building data pipelines, testing environments, or high-fidelity simulations to train and stress-test algorithms before they scale.
• Cross-Domain Integration: Working with perception, CV, and backend teams to ingest complex data streams and output precise, reliable system commands or insights.
• Applied Research: Adapting state-of-the-art papers in Deep Learning, Reinforcement Learning, NLP/LLMs, or Control Systems into production-ready code.

Qualifications

• ML Theory: Strong skills in machine learning theory, deep learning model development, and modern AI architectures.
• Technical Stack: Proficiency in Python and experience with frameworks such as PyTorch or Tensor
• Flow.
• Deployment Knowledge: Understanding of data processing pipelines, model deployment (Cloud or Edge), and performance optimization.
• Engineering Standards: Experience with version control (Git), CI/CD, and Linux-based environments.
• Environment Familiarity: Familiarity with modern computation, cloud, or edge environments (e.g., GCP, AWS, Azure, SLURM, or hardware accelerators).
• Problem Solving: Excellent analytical skills with strong attention to detail and a collaborative mindset.
• Preferred Extras:
• Platform & Application AI: Experience building applications with Large Language Models (LLMs), agentic workflows, or handling large-scale cloud data infrastructure.
• Algorithm & Edge Specialization: Experience in Reinforcement Learning (RL), Control Systems, Sequential Decision Making, or Signal Processing.
• Hardware-Aware AI: Experience with real-time inference optimization (e.g., TensorRT, quantization, pruning) for constrained environments.
• Low-level

Skills

• Proficiency in C++ or experience with custom CUDA kernels.
• Industry Experience: Previous experience working within or for Def
• Sec (Defense & Security) companies.
• Why join Nest
• AIAt Nest
• AI, you’ll build meaningful, real-world technology as part of a world-class team of engineers, scientists, and experienced professionals.
• You’ll work on systems where reliability genuinely matters, contribute to Europe’s security and resilience, and solve problems that demand depth, trust, and craftsmanship.
• If you want to build with purpose — and with leading experts in the field — you’ve come to the right place.
• Perks &

Benefits

We offer a growing set of practical benefits to support your work and wellbeing, day to day:

Occupational healthcare (currently provided by Mehiläinen)Epassi Flex benefit (sports, culture, commuting, wellbeing)Lunch benefit (25% tax-free coverage)Regular team lunches and all-hands eventsYour choice of Mac or PCHoliday allowance (50% of holiday salary)Phone benefit according to company policy (subscription and device)We are continuously developing and expanding our benefits as we grow.

PracticalitiesEmployment is subject to applicable security clearance (TURSEL).

NestAI is an equal opportunity employer. We consider all applicants based on their skills, experience, and potential.