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- Tasks: Design and implement cutting-edge machine learning systems and pipelines.
- Company: Join a forward-thinking tech company in London with a hybrid work model.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact by innovating with the latest machine learning technologies.
- Qualifications: Bachelor's degree and 8+ years of experience in machine learning and software development.
- Other info: Collaborative environment with a focus on continuous learning and staying ahead in tech.
The predicted salary is between 48000 - 72000 £ per year.
Location: London, UK
Work Mode: Hybrid (Weekly twice)
Job Description:
- Redis cluster setup
- Kafka/Flink streaming pipelines
- S3 Data pipeline
- Real time micro batches implementation (5 minutes, hourly, daily)
- Mongo/Atlas as alternative implementation (we might land with S3 instead)
- SageMaker MLOps / SageMaker Training / SM Model Deployment
- Pytorch
- Design machine learning systems: You will work on building and implementing machine learning models and deploying these models into production.
- Data analysis: You will be responsible for improving data quality through data cleaning, validation, and transformation so that it can be used effectively by the machine learning models.
- Educate the team: As our machine learning expert, you will also have the opportunity to teach others about machine learning principles and help them understand how these principles can be applied to our products.
- Stay updated: You should stay abreast of latest trends and developments in machine learning, ensuring we continue to innovate.
Qualifications:
- Bachelor's Degree in Computer Science, Statistics, Applied Math or related field.
- 8+ years of practical experience with machine learning, algorithm design, data modeling, and software development.
- Hands-on experience in machine learning, predictive modeling and analysis, and cross-functional collaboration.
- Proficient in Python, R, Java or C++ programming languages.
- Experience with Hadoop, Hive, Spark, SQL or other big data technologies.
- Excellent communication skills, as this role will collaborate with both technical and non-technical colleagues.
Machine Learning Engineer employer: Natobotics
Contact Detail:
Natobotics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the machine learning field, attend meetups, and join online forums. The more people you know, the better your chances of landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving real-time data pipelines or model deployment. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with tools like SageMaker and Pytorch, and don’t forget to highlight your ability to educate others about machine learning.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Make sure to tailor your application to reflect your passion for machine learning and how you can contribute to our innovative projects.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning, data pipelines, and the specific technologies mentioned in the job description. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about machine learning and how you can contribute to our team. Share specific examples of your past work that relate to the role – we love a good story!
Show Off Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to mention them. We’re keen to see your hands-on experience with tools like SageMaker, Pytorch, or any data pipeline setups you've done.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Natobotics
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, R, and big data tools. Brush up on your experience with Kafka, Flink, and SageMaker, as these will likely come up during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've implemented machine learning models. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Communicate Clearly
Since this role involves collaboration with both technical and non-technical colleagues, practice explaining complex concepts in simple terms. This will show that you can educate others and work effectively within a team.
✨Stay Current
Research the latest trends in machine learning and be prepared to discuss them. Showing that you’re proactive about staying updated will impress the interviewers and highlight your passion for the field.
