Deep Learning Engineer (Robotics)

TL;DR

Deep Learning Engineer (AI/Robotics): Training and fine-tuning VLA policies for hirify.global robots with an accent on behaviour cloning, RL, and large-scale data pipeline development. Focus on scaling distributed training, optimizing neural network architectures for edge inference, and managing complex multimodal data.

Location: London, UK (Onsite)

Company

hirify.global is a UK-based robotics startup developing advanced, commercially scalable hirify.global robots integrated for industrial and daily life applications.

What you will do

• Post-train policies via behaviour cloning and RL for robot movement.
• Partner with Data Collection teams to curate balanced, high-quality pretraining datasets.
• Run pre-, mid-, and post-training on VLA stacks while exploring new architectures.
• Build continuous pipelines for synthetic data ingestion, versioning, and weak-supervision.
• Collaborate with MLOps and Data Platform teams to scale distributed training.
• Optimize deep learning models for real-time edge inference on robotic hardware.

Requirements

• 3+ years of experience building deep-learning systems in industry or research.
• Hands-on experience with LLMs, VLMs, or image/video generative models.
• Strong expertise in Python and deep learning frameworks like PyTorch or JAX.
• Experience with deep learning infrastructure, including streaming datasets and distributed training.
• Familiarity with modern software engineering practices and clear technical documentation.

Nice to have

• Robotics or autonomous driving experience.
• Experience applying RL to LLMs or robotics.
• Knowledge of OpenVLA, Physical Intelligence (π) models, or similar frameworks.
• Proven productization of deep nets with latency and throughput constraints.
• Publications at top-tier deep learning conferences or open-source contributions.

Culture & Benefits

• Competitive salary with participation in a Stock Option Plan.
• Paid vacation compliant with local labor laws.
• Travel opportunities to company offices in Vancouver and Boston.
• Office perks including free meals and team events.
• Startup environment emphasizing speed, transparency, and minimal bureaucracy.