At a Glance
- Tasks: Lead the development of cutting-edge machine learning solutions and optimise AI models.
- Company: Exciting AI software company focused on solving real-world problems.
- Benefits: Competitive salary up to £200,000, remote work, and opportunities for professional growth.
- Other info: Join a dynamic team with a focus on collaboration and career advancement.
- Why this job: Make a real impact in AI while working with innovative technologies and talented teams.
- Qualifications: Proven experience in machine learning systems and strong software engineering skills.
The predicted salary is between 100000 - 200000 £ per year.
Full Time Remote London, UK (Remote)Posted 1 day ago100,000 - 200,000 GBP / Year Staff Machine Learning Engineer | Remote | Salary 100,000-200,000 (flexible)Hexwired Recruitment has partnered with an exciting AI software company developing advanced machine learning products that solve complex, real-world problems.
They’re looking for a Technical Lead to bridge research and engineering, taking cutting-edge models from experimentation into robust production systems.
The Role This is a senior hands-on leadership position where you’ll own the execution of the company’s machine learning platform, working closely with research, software engineering and product teams to build scalable, production-grade AI solutions.
Responsibilities Own the end-to-end machine learning lifecycle, including data pipelines, model training, evaluation, inference and deployment.
Fine-tune and optimise large language models using modern techniques such as Lo RA, QLo RA, supervised fine-tuning, preference optimisation and model distillation.
Design scalable inference infrastructure with a focus on latency, reliability and operational efficiency.
Build and maintain high-quality data pipelines for both synthetic and real-world datasets.
Develop robust evaluation frameworks covering model quality, robustness, safety and performance.
Optimise GPU utilisation, memory usage and inference performance for production deployments.
Work closely with software engineers to integrate ML capabilities into backend services and customer-facing products.
Lead technical delivery, mentor engineers and help shape engineering best practices.
Balance research ambitions with practical engineering trade-offs to deliver value quickly.
Technology Python Py Torch and/or JAXLarge-scale GPU training and inference infrastructure Modern ML deployment pipelines Ideal Experience Proven experience delivering machine learning systems into production.
Strong understanding of modern foundation models and large language models.
Experience building scalable training and inference infrastructure.
Excellent software engineering skills with a focus on maintainable, production-quality code.
Comfortable leading technical delivery while remaining hands-on.
Strong communication skills and the ability to collaborate across research, engineering and product teams.
If you are an experienced Staff Machine Learning Engineer looking for a new remote opportunity paying a market-leading salary up to 200,000.
To be considered for this role apply to this remote Staff Machine Learning Engineer job.
For more information on this role, or any other jobs across; Embedded, C++ programming, Embedded Linux, Golang Development, FPGA, Python, Javascript, C#, Electronics, Secure Boot, Power Electronics, Digital Design, Machine Learning, Data Science or Simulation contact us today.
Tagged as: Machine Learning, Python, Software
Staff Machine Learning Engineer employer: Hexwired Recruitment
As a Senior FPGA Engineer, you will thrive in a dynamic and innovative environment that values creativity and technical expertise. Our company offers competitive salaries, comprehensive benefits, and a strong commitment to employee development, ensuring you have the resources and opportunities to grow your career. Located in a vibrant tech hub, we foster a collaborative work culture that encourages teamwork and the sharing of ideas, making it an exciting place to contribute to cutting-edge projects.
