Hands-On ML Team Lead for Scalable Production Models

Omnis Partners Ltd.; United Kingdom; On-site; GBP 92,000 - 166,000; Full time

Job summary

Omnis Partners Ltd. is seeking an experienced Machine Learning Team Lead in the United Kingdom to join a highly technical ML team on an initial 6‑month contract. The role combines leadership with close involvement in architecture, training, and optimisation of cutting‑edge ML models.

You will lead ML Engineers, guide deployments from research to production, and work on transformer architectures and large‑scale distributed training. Quick availability is desirable for ASAP start.

Qualifications

• Strong experience leading / line managing ML Engineers.
• Deep technical background in Machine Learning & Deep Learning.
• Experience building, training and fine-tuning models, including working with modern transformer architectures.
• Strong knowledge of distributed training and large-scale ML.
• Experience with inference and model optimisation.
• Proven experience taking models from research/development through to production at scale.

Responsibilities

• Lead and mentor a team of ML Engineers while staying hands-on with architecture, training and optimisation of models.
• Drive productionisation of ML solutions from research to scalable deployments.
• Collaborate with cross-functional teams on architecture decisions and performance improvements.

Skills

Leadership

ML & DL

Model training

Transformers

Distributed training

Model optimization

Production deployment

Software fundamentals

Startup experience

Job description

Omnis Partners Ltd. is seeking an experienced Machine Learning Team Lead in the United Kingdom to join a highly technical ML team on an initial 6‑month contract. The role combines leadership with close involvement in architecture, training, and optimisation of cutting‑edge ML models.

You will lead ML Engineers, guide deployments from research to production, and work on transformer architectures and large‑scale distributed training. Quick availability is desirable for ASAP start.