Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Optimise machine learning systems and enhance AI software's predictive capabilities.
- Company: Leading tech firm in London focused on innovation and collaboration.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Exciting projects with potential for career advancement in a fast-paced environment.
- Why this job: Join a dynamic team and make a real impact in the world of AI.
- Qualifications: Bachelor's degree in relevant field and experience in machine learning.
The predicted salary is between 55000 - 70000 £ per year.
We are looking for a highly capable machine learning engineer to optimize our machine learning systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities. To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.
Machine Learning Engineer Responsibilities
- Consulting with managers to determine and refine machine learning objectives.
- Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
- Transforming data science prototypes and applying appropriate ML algorithms and tools.
- Ensuring that algorithms generate accurate user recommendations.
- Turning unstructured data into useful information by auto-tagging images and text‑to‑speech conversions.
- Solving complex problems with multi‑layered data sets, as well as optimizing existing machine learning libraries and frameworks.
- Developing ML algorithms to analyze huge volumes of historical data to make predictions.
- Running tests, performing statistical analysis, and interpreting test results.
- Documenting machine learning processes.
- Keeping abreast of developments in machine learning.
Machine Learning Engineer Requirements
- Bachelor's degree in computer science, data science, mathematics, or a related field.
- Master’s degree in computational linguistics, data analytics, or similar will be advantageous.
- At least two years' experience as a machine learning engineer.
- Advanced proficiency with Python, Java, and R code writing.
- Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
- In-depth knowledge of mathematics, statistics, and algorithms.
- Superb analytical and problem‑solving abilities.
- Great communication and collaboration skills.
- Excellent time management and organizational abilities.
Big Data Engineer employer: Trinitysoft Solutions
Contact Detail:
Trinitysoft Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Big Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Big Data Engineers on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and any cool algorithms you've developed. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML interview questions and be ready to discuss your past experiences and how they relate to the role you're applying for.
✨Tip Number 4
Don't forget to apply through our website! We make it super easy for you to find and apply for roles that match your skills. Plus, it shows us you're genuinely interested in joining our team!
We think you need these skills to ace Big Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Big Data Engineer role. Highlight your experience with machine learning systems, Python, and any relevant projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background makes you a great fit for us. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any cool machine learning projects, make sure to mention them! Whether it's a personal project or something from your previous job, we love seeing practical applications of your skills.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. We can’t wait to hear from you!
How to prepare for a job interview at Trinitysoft Solutions
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and algorithms. Be ready to discuss specific frameworks and libraries you've worked with, as well as how you've applied them in real-world scenarios. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've solved using data science. Think of examples where you transformed unstructured data into actionable insights or optimised existing ML processes. Use the STAR method (Situation, Task, Action, Result) to structure your answers clearly.
✨Communicate Clearly
Since collaboration is key in this role, practice explaining your technical work in simple terms. You might be asked to explain a complex algorithm or process to someone without a technical background, so being able to communicate effectively is crucial.
✨Stay Updated
Demonstrate your passion for machine learning by discussing recent developments in the field. Mention any new tools or techniques you've learned about and how they could potentially benefit the company. This shows you're proactive and committed to continuous learning.