Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our machine learning team to enhance speech recognition models and optimise training pipelines.
- Company: Be part of an innovative tech company pushing the boundaries of AI and machine learning.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Work on cutting-edge technology that impacts real-world applications and enhances user experiences.
- Qualifications: Master's or PhD in a relevant field with strong foundations in machine learning required.
- Other info: Ideal for tech enthusiasts eager to stay ahead in the fast-evolving AI landscape.
The predicted salary is between 48000 - 72000 £ per year.
Work within our clients machine learning team to deploy and optimize models for applications like low-latency speech recognition and large language models (LLMs). Initial focus will be on improving our clients speech recognition model's training pipeline on multi-GPU systems to boost performance and quality.
Responsibilities:
- Train and deploy state-of-the-art ML models.
- Apply optimization techniques (distillation, pruning, quantization).
- Enhance speech models with features such as diarization, multilingual support, and keyword boosting.
- Optimize models for low-latency inference on accelerators.
- Improve training workflows and GPU utilization.
- Use data augmentation to improve performance.
- Stay updated on ML research to guide strategy.
Requirements:
- Master's or PhD in a relevant field with strong ML foundations.
- Training ML models for production use.
- PyTorch or TensorFlow.
- Handling large datasets (multi-terabyte).
- Familiarity with Linux, version control, and CI/CD systems.
- Knowledge of model compression (e.g., reduced precision).
Machine Learning Engineer employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in speech recognition and large language models. This will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the machine learning community by attending relevant meetups, webinars, or conferences. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for job openings.
✨Tip Number 3
Showcase your practical experience with PyTorch or TensorFlow through personal projects or contributions to open-source initiatives. Having a portfolio that highlights your skills in deploying and optimising ML models can set you apart from other candidates.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges related to machine learning algorithms and optimisation techniques. Being well-versed in these areas will boost your confidence and performance during the interview process.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with PyTorch or TensorFlow. Include specific projects where you've trained ML models for production use and mention any work with large datasets.
Craft a Strong Cover Letter: In your cover letter, express your passion for machine learning and detail how your skills align with the responsibilities listed in the job description. Mention your familiarity with optimization techniques like distillation and pruning, as well as your experience with low-latency inference.
Showcase Relevant Projects: If you have worked on projects involving speech recognition or model compression, be sure to include these in your application. Describe your role and the impact of your contributions, especially in improving training workflows or GPU utilization.
Highlight Continuous Learning: Mention any recent courses, certifications, or research you’ve engaged in related to machine learning. This shows your commitment to staying updated on ML research and your proactive approach to professional development.
How to prepare for a job interview at Microtech Global Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with PyTorch or TensorFlow in detail. Highlight specific projects where you've trained ML models for production use, especially those involving large datasets and multi-GPU systems.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your ability to apply optimization techniques like distillation, pruning, and quantization. Prepare examples of how you've improved model performance or training workflows in past roles.
✨Stay Current with ML Research
Familiarise yourself with the latest advancements in machine learning, particularly in speech recognition and large language models. Being able to discuss recent research can show your passion and commitment to the field.
✨Prepare for Practical Assessments
You may be asked to solve a practical problem or complete a coding challenge during the interview. Brush up on your coding skills and be ready to demonstrate your understanding of model compression and GPU utilisation.
