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- Tasks: Lead the development of cutting-edge ML solutions for FinTech and RegTech products.
- Company: Join a renowned international client making waves in the tech industry.
- Benefits: Enjoy hybrid or remote work options and a competitive salary package.
- Why this job: Be at the forefront of analytics and intelligence in a dynamic, innovative environment.
- Qualifications: Experience with JVM languages, Python NLP, ML-Ops, and cloud platforms is essential.
- Other info: Ideal candidates will have a strong grasp of ML algorithms and data analysis techniques.
The predicted salary is between 96000 - 168000 £ per year.
Lead Machine Learning Engineer or Senior ML Engineer required by my extremely well known client based on a Hybrid or remote working basis. As a Lead ML / Machine Learning Engineer you will play a big part in driving my clients analytics and intelligence which drive their FinTech and RegTech products. My well known International client is looking for someone who has experience of; JVM language (Java/Kotlin) and experience in Python NLP, ML-Ops and data pipelines ML frameworks/libraries such as TensorFlow, PyTorch, scikit-learn Cloud platforms like Amazon Web Services & Google Cloud Kafka and RDBMS such as MySQL & Postgres Ideally you will also have a strong understanding of ML Algorithms, Statistical techniques, and data analysis methodologies. In return for these strong ML skills and experience, my large International client is looking to reward the right candidate with a great package. This is to include a great basic salary of between £120,00 – £140,000 per y…
Lead Machine Learning Engineer employer: Launch IT Recruitment
Contact Detail:
Launch IT Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with JVM languages like Java or Kotlin. Highlight any projects where you've utilized these languages, especially in the context of machine learning or data pipelines.
✨Tip Number 2
Demonstrate your proficiency in Python, particularly with NLP and ML frameworks such as TensorFlow or PyTorch. Consider discussing specific applications or results you've achieved using these tools.
✨Tip Number 3
Familiarize yourself with cloud platforms like AWS and Google Cloud. If you have experience deploying machine learning models on these platforms, be ready to discuss your approach and any challenges you overcame.
✨Tip Number 4
Brush up on your knowledge of ML algorithms and statistical techniques. Be prepared to explain how you've applied these methodologies in past projects, as this will demonstrate your analytical skills and depth of understanding.
We think you need these skills to ace Lead Machine Learning Engineer
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience with JVM languages like Java or Kotlin, as well as your proficiency in Python, especially in NLP and ML-Ops. Tailor your CV to showcase projects where you've utilized these skills.
Showcase Your Technical Skills: Detail your familiarity with ML frameworks such as TensorFlow, PyTorch, and scikit-learn. Include specific examples of how you've implemented these technologies in past roles to drive analytics and intelligence.
Demonstrate Cloud Knowledge: Mention your experience with cloud platforms like AWS and Google Cloud. If you have worked on data pipelines or deployed machine learning models in the cloud, be sure to include those details.
Include Statistical Techniques: Discuss your understanding of ML algorithms and statistical techniques. Provide examples of how you've applied data analysis methodologies in your previous work to solve complex problems.
How to prepare for a job interview at Launch IT Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with JVM languages like Java or Kotlin, as well as your proficiency in Python, especially in NLP. Highlight specific projects where you've utilized these technologies.
✨Demonstrate Your ML Knowledge
Make sure to articulate your understanding of machine learning algorithms and statistical techniques. Be ready to explain how you've applied these concepts in real-world scenarios, particularly in FinTech or RegTech.
✨Discuss Your Experience with Data Pipelines
Talk about your experience with ML-Ops and data pipelines. Mention any frameworks or libraries you've used, such as TensorFlow or PyTorch, and how they contributed to the success of your projects.
✨Familiarize Yourself with Cloud Platforms
Since the role involves working with cloud platforms like AWS and Google Cloud, be prepared to discuss your experience with these services. Share examples of how you've leveraged cloud technologies to enhance your machine learning solutions.
