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- Tasks: Design and build software for Machine Learning systems while collaborating with clients.
- Company: Join a leading London-based IT consultancy focused on innovative tech solutions.
- Benefits: Enjoy fully remote work with a flexible contract and potential for extension.
- Why this job: Be at the forefront of ML technology, working with experts in a dynamic environment.
- Qualifications: Experience with ML frameworks, Python, and cloud services like AWS or GCP required.
- Other info: This role offers a chance to make a real impact in the tech industry.
The predicted salary is between 42000 - 84000 £ per year.
Job Title: Machine Learning Engineer
Location: Fully Remote UK
Job Type: 6 Month Contract + chance for extension
Interview Process: Video Interviews held remotely
Rate: DOE Outside IR35
A Private Equity firm are seeking a Machine Learning Engineer to join on an initial 6-month contract to assist in the firms portfolio optimisation, risk management, and predictive modelling. You will be working alongside them through one of our consultancy partners who have recently won the bid for the project.
The end point client operate primarily in an Azure environment hence demonstratable experience in Azure is a must.
Machine Learning Engineer Key Responsibilities:
- Use generative AI to build predictive models for market trends, asset valuation, and investment opportunities.
- Leverage AI algorithms for portfolio optimisation, risk analysis, and asset allocation strategies.
- Automate data extraction and analysis from financial reports, news, and alternative data sources to support investment decisions.
- Use AI to simulate different market conditions and generate optimal exit strategies.
- Help in the adoption of AI tools to optimise operations, reduce costs, and drive growth through automation and data-driven insights.
Machine Learning Engineer Key Skills Required:
- Comprehensive understanding of the full machine learning lifecycle, from development to production.
- Experience deploying machine learning models using frameworks like Scikit-learn, TensorFlow, or PyTorch.
- Proficiency in Python and adherence to software engineering best practices.
- Strong technical expertise in cloud architecture, security, and deployment, with experience in Azure.
- Hands-on experience with containers, particularly Docker and Kubernetes.
- Solid foundation in probability, statistics, and common supervised and unsupervised learning techniques.
If you think this could be an exciting opportunity for you then please apply now!
Machine Learning Engineer employer: X4 Technology
Contact Detail:
X4 Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with the full machine learning lifecycle. Be ready to discuss specific projects where you designed, built, and deployed ML systems, as this will demonstrate your comprehensive understanding of the role.
✨Tip Number 2
Familiarize yourself with the latest trends and best practices in machine learning deployment. Being able to talk about scalable tools and frameworks like Scikit-learn, TensorFlow, or PyTorch will set you apart during the interview.
✨Tip Number 3
Highlight your collaboration skills. Since the role involves working closely with customers and data scientists, be prepared to share examples of how you've successfully partnered with others to deliver tailored solutions.
✨Tip Number 4
Brush up on your cloud architecture knowledge, especially if you have experience with AWS, GCP, or Azure. Discussing your hands-on experience with containers like Docker and Kubernetes will also show that you're well-versed in modern deployment practices.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Machine Learning Engineer position. Understand the key responsibilities and required skills, so you can tailor your application accordingly.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience with machine learning frameworks like Scikit-learn, TensorFlow, or PyTorch. Provide specific examples of projects where you've deployed machine learning models.
Showcase Technical Skills: Clearly outline your proficiency in Python and any relevant cloud platforms (AWS, GCP, Azure) in your application. Mention your experience with containers like Docker and Kubernetes, as these are crucial for the role.
Tailor Your Cover Letter: Write a personalized cover letter that addresses how your skills and experiences align with the company's needs. Discuss your understanding of the machine learning lifecycle and your approach to operationalizing ML software.
How to prepare for a job interview at X4 Technology
✨Showcase Your Machine Learning Knowledge
Be prepared to discuss the full machine learning lifecycle. Highlight your experience with frameworks like Scikit-learn, TensorFlow, or PyTorch, and be ready to explain how you've deployed models in past projects.
✨Demonstrate Your Technical Skills
Make sure to emphasize your proficiency in Python and your understanding of software engineering best practices. Discuss any relevant experience you have with cloud platforms like AWS, GCP, or Azure, as well as your familiarity with containers such as Docker and Kubernetes.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and ability to collaborate with data scientists and engineers. Think of examples where you've successfully partnered with others to deliver tailored ML solutions.
✨Understand the Company's Needs
Research the consultancy's projects and clients to understand their specific requirements. Be ready to discuss how your skills can help operationalize ML software for real-world applications, aligning your answers with their goals.
