ML Team Lead - Mentor Engineers & Deliver Scalable Models

Speechmatics; London (KY); Hybrid; USD 172,000 - 238,000; Full time

Benefits offered by this job

Private Medical

Dental insurance

Pension/401K matching

Home office stipend

Parental leave support

Global mobility

Job summary

Speechmatics is seeking an experienced leader to guide and mentor a world-class ML engineering team. You will provide technical oversight for end-to-end ML development, ensuring robust, scalable solutions while promoting software engineering best practices.

The role requires coordinating resources across teams to align with business objectives and drive production-ready ML systems. The ideal candidate has a strong track record deploying models at scale, deep knowledge of transformer

Qualifications

• Proven experience guiding and mentoring ML engineers.
• Prioritizes work by impact, feasibility, and time-to-value with clear success metrics.
• Deep understanding of modern ML stack, transformers, distributed training, and inference optimizations.
• Track record deploying models at scale and collaborating across teams.

Responsibilities

• Lead, mentor, and grow a world-class team of ML engineers through coaching and professional development.
• Provide technical oversight for end-to-end ML development, ensuring robust, scalable solutions.
• Guide adoption of best software engineering practices across the ML team.
• Plan work, allocate resources, and collaborate cross-functionally to align with business goals.
• Drive the technical work to deliver high-quality ML solutions that meet strategic targets.

Skills

Mentor ML engineers

Guiding team

Transformer architectures

Distributed training

Model inference optimization

Python

TensorFlow

PyTorch

Cloud platforms

ML testing frameworks

Software engineering practices

Tools

TensorFlow

PyTorch

Python

Job description

Speechmatics is seeking an experienced leader to guide and mentor a world-class ML engineering team. You will provide technical oversight for end-to-end ML development, ensuring robust, scalable solutions while promoting software engineering best practices.

The role requires coordinating resources across teams to align with business objectives and drive production-ready ML systems. The ideal candidate has a strong track record deploying models at scale, deep knowledge of transformer