Senior AI / ML Engineer – Autonomous Systems

📍 Stockholm, Sweden

✈ Travel required

Build the AI Core of a Real-World Autonomy System

Do you want to develop AI that enables drones to see, understand, and act?

Tiepoint is building a distributed autonomy environment across Norway and Sweden — combining cybernetics, AI, and real-world drone operations.

• Andenes: Cybernetics & flight systems engineering
• Skien: Drone operations & large-scale data collection
• Stockholm: AI architecture & autonomy engineering

Our systems are developed for demanding operational environments — Arctic cold, constrained bandwidth, strict safety requirements, and unpredictable real-world conditions.

This is not a pure computer vision role.

This is not a research-only position.

This is applied autonomy engineering.

We are now strengthening our Stockholm AI core with a Senior AI / ML Engineer who will work directly with our Head of AI on advanced autonomy systems.

The Mission

In Stockholm, we build the AI core — the layer that connects perception, control, and mission-level behaviour.

You will contribute to systems that:

• Interpret dynamic environments
• Make constrained decisions
• Operate under latency and hardware limitations
• Transition reliably from simulation to field deployment

This role operates above the perception layer and collaborates closely with operational and cybernetics teams in Norway.

What You Will Work On

• Learning-based guidance and decision algorithms
• Reinforcement learning for constrained autonomy
• Edge-optimised inference and real-time execution
• System-level AI architecture
• Simulation-driven validation and sim-to-real workflows
• Robust training and deployment pipelines (MLOps)

You will work across the full lifecycle:

Architecture → Model design → Training → Optimisation → Deployment → Field validation → Iteration

You must be equally comfortable prototyping in Python and debugging performance on embedded hardware.

What We Are Looking For

You likely have:

• 5+ years of applied AI/ML engineering experience
• Strong Python skills
• Experience with PyTorch and/or TensorFlow
• Experience deploying ML systems into production
• Experience with reinforcement learning for control or constrained environments
• Strong system-level thinking

Strong advantages:

• Robotics or autonomous systems experience
• Edge AI / embedded deployment
• Real-time systems
• Simulation environments (Gazebo, Isaac Sim, similar)
• MLOps and CI/CD for ML
• Experience from robotics, aerospace, or defence-related domains

The Profile We Value

You think in systems — not just models.

You understand that:

• Latency budgets matter
• Deterministic behaviour matters
• Hardware constraints matter
• Field performance matters more than benchmark scores

You are comfortable in a small, technically ambitious team where ownership is real, and impact is visible.

You are motivated by building AI that operates outside the lab.

Security Clearance Requirement

This role requires eligibility for Norwegian security clearance in accordance with the Norwegian Security Act (Sikkerhetsloven).

Security clearance assessments are conducted by the relevant national authorities and may involve a review of the candidate’s background, including residential history. As part of this process, documented, continuous residence — typically within NATO/EU countries — over the past 10 years may significantly facilitate clearance processing.

Due to project timelines and anticipated clearance requirements, candidates should normally be able to document this residential history. Individual circumstances will be assessed in accordance with applicable laws and regulations.

Strong English skills are required.

Scandinavian language skills are an advantage.

Why Join Tiepoint?

• Central role in building a Nordic autonomy environment
• Direct collaboration with cybernetics and operational teams
• High architectural influence
• Competitive compensation
• Hybrid flexibility in Stockholm
• Real-world impact in defence and security applications

If you are interested in building production-grade autonomy systems — not just training models — we would like to hear from you.