AI Research Engineer – Machine Learning Engineering

About Helsing

Helsing is dedicated to advancing defence capabilities through AI, striving to ensure that democratic societies remain self-governing and uphold ethical values. The organization fosters an inclusive, transparent atmosphere where robust discussions on technology's impact in defence are encouraged.

Role Summary

You will help drive the development of autonomously enabled decision-making systems for defence. This involves the full spectrum of AI technologies, including large-scale data handling, reinforcement learning (RL), and the development of foundational models. You'll contribute as a key member of a cross-disciplinary team, focusing on creating and optimizing distributed systems to maximize performance for AI training and increase developer productivity. Your expertise should bridge machine learning and systems engineering, facilitating scalable, reliable AI infrastructure.

Main Responsibilities

• Expand and enhance highly integrated deep learning frameworks (built on PyTorch) to ensure they are efficient and adaptable across varied use cases.
• Optimize and scale existing infrastructure and tools to enable faster, more extensive distributed training workloads.
• Devise data strategies that facilitate large dataset processing and storage efficiency, ensuring GPU resources are utilized effectively.

Core Requirements

• Graduate degree (MSc or PhD) in Computer Science or a related STEM area, specializing in machine learning and deep learning.
• Proficient software engineering abilities in Python; extensive knowledge of modern deep learning frameworks (PyTorch, JAX, or TensorFlow), with experience in creating custom components and distributed training scripts.
• Strong communication skills with the ability to convey complex theoretical concepts clearly and to strengthen the internal engineering community.
• Approach problems from first principles and stay current on cutting-edge AI optimization techniques, swiftly incorporating them into working solutions.
• Practical experience debugging and optimizing production ML pipelines, especially with regard to nuanced numerical or performance issues.

Preferred Qualifications

• Hands-on practice training models on distributed GPU clusters, familiarity with advanced parallelization strategies and inter-node communication protocols (such as NCCL or MPI).
• Experience working with heterogeneous, large-scale datasets, understanding the intricacies of locality, encoding, formatting, and streaming methodologies.
• Competence with workload orchestration tools (e.g., Slurm, Kubernetes, Ray) for scheduling and managing complex training jobs.
• Insight into GPU internal architectures, including memory hierarchies, execution patterns, and distinctions between training- and inference-oriented workloads.

Work Environment and Culture

• Opportunity to contribute directly to technologically safeguarding democratic nations, addressing significant ethical and geopolitical concerns.
• Exposure to unique technical challenges requiring robust, innovative engineering in a high-impact environment.
• Work alongside world-class experts in AI and engineering.
• Encouragement of critical thinking, outcome-driven approaches, and responsible autonomy, with space for all voices and perspectives in decision-making.

Benefits

• Competitive salary and equity participation (VSOP) options.
• Relocation assistance up to €2,500 and up to four weeks’ temporary accommodation.
• Annual learning budget (€500/£450).
• Health and wellness perks (gym membership, mental health support via Nilo.health).
• Regular company events and monthly social benefits.
• Enhanced parental leave benefits (22 weeks fully paid for primary caregivers, 6 weeks for secondary caregivers).
• Family-friendly policies, including five days paid emergency leave, remote work options during pregnancy, and phased return-to-work.
• Comprehensive onboarding with special focus on familiarizing new hires with in-house tools, ML pipelines, and cross-team collaboration from day one.

Additional Information

Helsing recognizes the underrepresentation of women and minority groups in this field and encourages candidates from all backgrounds to apply, even if all requirements are not met. The company is committed to equality of opportunity and upholds a strict policy regarding the handling of sensitive personal data. Additional or region-specific benefits may be available.