Senior AI Engineer - Applied Scientist

About Forterra

At Forterra, we are unleashing autonomy at scale to transform the battlefield. Our mission is to build the foundational platforms that enable an intelligent ecosystem to coordinate, adapt, and execute with speed and precision even in the uncertainty and disruption of modern conflict. In an era marked by rapid technological change and evolving threats, we design for flexibility, survivability, and operational dominance.

Forterra delivers weapons, sensors, and battlefield effects through integrated autonomous networks reaching operational areas faster, safer, and without placing human lives at risk. Our systems operate with distributed control, dynamic routing, and real-time responsiveness, enabling sustained advantage across complex mission environments.

About The Role 

We are seeking a Senior/Staff AI Engineer with deep expertise in generative modeling and multimodal AI systems. In this role, you will design and implement advanced models for understanding complex agent interactions in dynamic environments. You'll work on extending these capabilities toward vision-language models and action-aware systems, collaborating closely with research and engineering teams to bridge foundational representation learning with real-world applications. 

What You'll Do 

• Develop neural network architectures for modeling sequential agent interactions using generative modeling approaches 

• Implement Transformer-based models that encode agent and contextual features with attention mechanisms for capturing interactions 

• Research and integrate goal-conditioned models that leverage structured representations before generating complete sequences 

• Prototype and optimize learning models into lightweight modules suitable for real-time inference 

• Collaborate with cross-functional teams to ensure seamless integration of models into the broader AI stack 

• Benchmark and visualize model performance using real-world and simulated datasets 

• Optimize models for low-latency inference and interpretability of output distributions 

Minimum Qualifications

• Deep understanding of probabilistic generative models for sequential forecasting tasks 

• Strong experience with Transformers and graph-based modeling for complex relational data 

• Familiarity with multimodal sensor processing and representation learning 

• Proven ability to work with uncertainty quantification and latent variable inference 

• Experience implementing models in PyTorch/TensorFlow and deploying them in production environments  

• M.S. or Ph.D. in Computer Science, Machine Learning, Robotics, or related field 

• 3+ years of experience with sequential modeling, generative architectures, or forecasting systems 

• Strong foundation in applied deep learning, especially variational inference and attention mechanisms 

• Solid software engineering background with emphasis on clean, modular, and optimized implementations 

Preferred Qualifications

• Publications or project experience in forecasting, agent modeling, or scene understanding 

• Familiarity with graph-based or vectorized representations of structured environments 

• Experience with diffusion model optimization or goal-conditioned decoding 

• Contributions to open-source frameworks related to generative modeling or sequential forecasting 

• Interest in bridging high-fidelity modeling with real-time applications 

US Salary Range
 $145,000—$185,000
 

The salary range for this role is an estimate and is based on a wide variety of compensation factors. The salary offered to candidates will vary based on a variety of factors including (but not limited to) relevant work experience, education, specialized training, critical expertise, training, and more. Equity in Forterra is included in most of our full-time, high-demand roles and is therefore considered part of Forterra’s overall compensation package. In addition to base salary and equity, Forterra offers competitive benefits for full-time employees including:

• Premium H