2 months ago
Bristol, United KingdomMid Level / Senior / Staff+
Responsibilities
- Own and ship ML systems from research through robust, maintainable production deployments, often on edge or embedded hardware.
- Train, fine-tune, evaluate, optimise, and adapt models for real-world use cases.
- Run and improve GPU-based training and inference workloads, including multi-GPU and multi-node environments.
- Profile, optimise, and debug model code, data pipelines, inference stacks, and hardware-constrained systems.
- Design evaluation pipelines, benchmarks, test sets, and feedback loops to assess model behaviour before and after deployment.
- Manage end-to-end data and ML workflows, including data collection, curation, feature engineering, training, deployment, monitoring, and iteration.
- Build MLOps and LLMOps capabilities including model CI/CD, containerisation, orchestration, experiment tracking, registries, safety guardrails, canaries, and performance monitoring.
- Establish batch and streaming data pipelines with strong curation, provenance, and reproducibility.
- Collaborate with software, systems, product, and customer teams, and mentor others or guide technical decisions depending on experience level.
Requirements
- Proven experience building, training, evaluating, optimising, or deploying ML systems for real-world use.
- Strong expertise in at least one major ML area such as optimisation, computer vision, sequence modelling, LLMs, probabilistic methods, model evaluation, or large-scale training.
- Strong grounding in machine learning and deep learning, including optimisation, generalisation, probability, and model architecture.
- Strong Python skills and sound software engineering practices including version control, testing, code review, debugging, and maintainability.
- Strong communication skills with the ability to mentor, influence, and explain technical topics to non-technical audiences.
- A degree, postgraduate study, or equivalent practical experience in machine learning, computer science, engineering, mathematics, or a related technical field.
- Experience with reproducible pipelines, model versioning, CI/CD, observability, automated evaluation, data engineering, or distributed model training is desirable.
- Experience with Databricks, Apache Spark, Delta Lake, MLflow, and SQL is desirable.
- A PhD in AI, ML, computer science, or a related field is beneficial.
- Candidates must be eligible for SC clearance; prior defence experience is not required.
Benefits
- Hybrid working with a minimum of three days per week on-site at the Bristol headquarters.
- Flexible working arrangements, including discussion of flexibility, part-time working requirements, and workplace adjustments.
- Inclusive workplace support through Rowden’s Disability Confident Committed status.
Tech Stack
Categories
About Rowden
Rowden builds mission-critical, real-time edge computing systems that turn advances in sensing, AI, and communications into operational capability in degraded or denied environments. It provides systems integration, software, and technology services to national security, defense, and critical industry customers, improving decision-making for frontline teams. Founded in 2017 and headquartered in Bristol, England, the privately held company operates over 20,000 square feet of engineering and manufacturing facilities.