Software Engineer, Applied ML - 2025

Brave; London; Hybrid; GBP 100,000 - 125,000; Full time

Job summary

A leading technology company in London seeks a Machine Learning Engineer to optimize and deploy ML models. The role involves collaboration across teams to implement innovative AI features and a focus on performance optimization. Offering competitive salary between £100,000 to £125,000 alongside flexible work arrangements. Ideal for problem solvers passionate about AI.

Benefits

Competitive compensation

Flexible work location

Opportunity to work with cutting-edge technology

Qualifications

• 2 to 5 years of experience optimizing and deploying ML models in production environments.
• Strong software engineering background with production experience.
• Extensive experience with PyTorch or other modern ML frameworks.
• Experience training custom models from scratch.

Responsibilities

• Generate synthetic data for training data augmentation.
• Collaborate with product and design teams to define new AI-powered features.
• Implement and optimize model serving infrastructure.
• Collaborate with DevOps teams on MLOps infrastructure.

Skills

Optimizing ML models

Software engineering

PyTorch experience

Model optimization

MLOps practices

Collaboration with DevOps teams

Education

Master's degree in Computer Science or related field

Tools

vLLM

ONNX Runtime

Nvidia Triton

Kubernetes

Job description

Summary

Core Responsibilities

• Generate synthetic data for training data augmentation and model evaluation
• Collaborate with product and design teams to define, prototype, and ship new AI-powered features including text-to-speech, image generation, and enhanced tool calling capabilities
• Implement and optimize model serving infrastructure using frameworks like vLLM, ONNX Runtime, and Nvidia Triton to achieve production-scale performance requirements
• Collaborate with DevOps teams on MLOps infrastructure including model monitoring, load testing, caching optimization, and automated CI/CD pipelines for model deployments
• Contribute to privacy-preserving ML approaches and on-device model implementations that align with Brave's privacy-first mission

Required Qualifications

• 2 to 5 years of experience optimizing and deploying ML models in production environments
• Strong software engineering background with production experience
• Extensive experience with PyTorch or other modern ML frameworks
• Experience training custom models from scratch
• Experience with model optimization and inference frameworks (e.g., vLLM, ONNX Runtime, Nvidia Triton)
• Familiarity with MLOps practices & Kubernetes and ability to collaborate with DevOps teams on model monitoring, load testing, and CI/CD pipelines
• Experience shipping ML-powered features or systems (consumer applications preferred)

Preferred Qualifications

• Master's degree in Computer Science, Machine Learning, or related field
• Familiarity with LLM serving frameworks (vLLM, TGI, Ray Serve) and GPU optimization
• Experience with embeddings, vector databases, semantic search implementations, model training workflows, and data pipeline development
• Experience integrating LLMs with tool calling/MCP
• Knowledge of privacy-preserving ML techniques and on-device model deployment
• Previous work on cost optimization and performance tuning of ML systems at scale

What We're Looking For

• Deep curiosity about emerging AI models and their practical applications
• Strong problem-solving skills with ability to work in ambiguous environments
• Excellence in cross-functional collaboration and technical communication
• Pragmatic approach to balancing innovation with shipping products

What We Offer

• Opportunity to shape the future of AI-powered browsing experiences
• Work with cutting-edge technology and state-of-the-art ML tools
• Competitive compensation with room for growth
• Great international exposure and team atmosphere
• Flexible work location with preference for London office

While we prefer candidates who can work from our London office, we're open to remote candidates in compatible time zones. We offer flexible working arrangements to support a healthy work-life balance.

Compensation

£100,000 to £125,000 (USD$125,000 to USD$155,000) - Depends on Location, Market Rate and Experience.

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