ML Engineer – Scalable Training & Model Development

About Us
Symbolica is an AI research lab pioneering the application of category theory to enable logical reasoning in machines.

We’re a well-resourced, nimble team of experts on a mission to bridge the gap between theoretical mathematics and cutting-edge technologies, creating symbolic reasoning models that think like humans – precise, logical, and interpretable. While others focus on scaling data-hungry neural networks, we’re building AI that understands the structures of thought, not just patterns in data.

Our approach combines rigorous research with fast-paced, results-driven execution. We’re reimagining the very foundations of intelligence while simultaneously developing product-focused machine learning models in a tight feedback loop, where research fuels application.

Founded in 2022, we’ve raised over $30M from leading Silicon Valley investors, including Khosla Ventures, General Catalyst, Abstract Ventures, and Day One Ventures, to push the boundaries of applying formal mathematics and logic to machine learning.

Our vision is to create AI systems that transform industries, empowering machines to solve humanity’s most complex challenges with precision and insight. Join us to redefine the future of AI by turning groundbreaking ideas into reality.

About the Role

As a Machine Learning Engineer, you’ll join a tight-knit team of experts at the cutting edge of model development — working on everything from dataset curation to scaling multi-node training runs. You’ll be responsible for turning research ideas into robust experiments, running massive sweeps, and closely tracking what works at the frontier of ML.

This is a role for someone who thrives in the messy middle between research and engineering — someone who can train models at scale, but also knows when to pause and question the next hyperparameter sweep. You’ll collaborate with researchers, MLOps, and evaluation engineers to accelerate the pace and quality of experimental progress.

📍 This is an onsite role based in our London office (66 City Rd).

Your Focus

• Own and run large-scale model training pipelines — from single-GPU prototyping to multi-node scaling
• Curate and manage dataset mixtures, including filtering, deduplication, and combining multiple sources
• Reproduce and rigorously test public baselines from recent papers
• Run controlled experimental sweeps, optimise for performance and stability at scale
• Explore and apply SoTA techniques: model distillation, synthetic data generation, parameter transfer, architectural tweaks
• Collaborate closely with MLOps to optimise training infrastructure and monitor runs
• Work hand-in-hand with model evaluation engineers to align training with meaningful metrics
• Support researchers in implementing new ideas and turning them into high-quality experiments
• Contribute to technical direction on model architecture and scaling strategy

About You

• Proficient hands-on experience training deep learning models, ideally at scale (multi-GPU, multi-node)
• Strong engineering skills in Python and PyTorch (or JAX); comfortable with distributed training setups
• Familiarity with dataset curation, versioning, and large-scale data management
• Hands-on experience running and analysing hyperparameter sweeps
• Deep curiosity about what’s happening at the research frontier — from LLM pretraining to distillation and beyond
• Comfort navigating research codebases and rapidly prototyping new ideas
• Bonus: experience with synthetic data, RLHF-style pipelines, or model scaling laws
• Comfortable in a fast-moving, collaborative environment with high levels of ownership and agency

What We Offer

• Competitive salary and early-stage equity package
• A chance to work at the intersection of cutting-edge research and robust engineering
• Ownership of training systems and direct impact on our model direction
• Collaborate with a team that values clarity, intellectual rigour, and hands-on experimentation

Read More About Symbolica

• https://fortune.com/2024/04/09/vinod-khosla-former-tesla-autopilot-engineer-ai-models/
• https://venturebeat.com/ai/move-over-deep-learning-symbolicas-structured-approach-could-transform-ai/

We are able to sponsor a Skilled Worker visa for qualified candidates applying to this position. This specific role exceeds the minimum salary threshold set by the UK government for Skilled Worker visa sponsorship. Please note that English language proficiency at B2 level or higher is required for this role.

Symbolica is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, or sexual orientation.