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- Tasks: Join our team to develop and optimise machine learning models for impactful business outcomes.
- Company: Qualient Solutions is a forward-thinking tech company based in London, focused on innovative solutions.
- Benefits: Enjoy hybrid work options, competitive pay, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that values creativity and collaboration while making a real difference.
- Qualifications: Bachelor's degree and 5 years' experience in business analysis, with strong analytical skills required.
- Other info: Active security clearance is a must; this role involves working with cutting-edge technology.
The predicted salary is between 48000 - 72000 £ per year.
Job Description
We at Qualient Solutions are looking for a Machine Learning Engineer based in London, UK.
Role Title: Machine Learning Engineer
Role Location: London, UK (Hybrid)
Role Type: Contract (inside ir35)
Must: Active Security Clearance
Job Summary:-
Responsibilities:
- Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed.
- Implement Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
- Ensure the models are modular. Ensure the model is source controlled with agreed release numbering.
- Extract any hard-coded elements and parameterise them so that the model execution can be controlled through input parameters.
- Ensure the model input parameters are version controlled and logged to the model execution runs for auditability.
- Ensure model metrics are logged to the model runs.
- Ensure model logging, monitoring, alerting to make sure any failure points are captured, monitored and alerted for support team to investigate or re-run of the model involves running of multiple experiments and chooses the best model (champion challenger) based on the accuracy/error rate of each experiment, ensure this is done in an automated manner.
- Ensure the model is triggered to run as per the defined schedule. If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies.
- Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future models to benefit.
- Where applicable, capture data drift, concept drift, model performance degradation signals and ensure model retrain.
- Implement CI/CD pipelines for ML models and automate the deployment.
- Maintain relevant documentation.
Requirements:
- Bachelor's degree in a relevant field.
- Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes.
- Strong understanding of banking and financial industry practices and regulations.
- Solid knowledge of Data Management process, data analysis and modelling techniques.
- Experience in monetary policy analysis (nice to have)
- Experience in time series database analysis
- Familiarity with Business Intelligence tools and concepts.
- Strong analytical and problem-solving skills.
- Experience in managing software development life cycles within Agile frameworks to ensure timely and high-quality delivery.
- Excellent communication and collaboration skills.
- Ability to adapt to changing requirements and priorities in a fast-paced environment.
Machine Learning Engineer employer: Qualient Technology Solutions UK Limited
Contact Detail:
Qualient Technology Solutions UK Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with Databricks best practices, as this role heavily involves building and maintaining ML pipelines. Understanding how to implement these practices will not only help you in interviews but also demonstrate your commitment to the role.
✨Tip Number 2
Brush up on your knowledge of CI/CD pipelines for ML models. Being able to discuss how you would automate deployment processes can set you apart from other candidates and show that you're ready to hit the ground running.
✨Tip Number 3
Since the role requires strong collaboration with Data Scientists, practice articulating your experience in teamwork and how you've successfully collaborated on projects in the past. This will highlight your ability to work effectively in a hybrid environment.
✨Tip Number 4
Given the importance of auditing and logging in this position, prepare examples of how you've implemented similar practices in previous roles. This will showcase your attention to detail and understanding of model governance.
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, data management, and any specific tools mentioned in the job description, such as Python, R, or MATLAB. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also demonstrates your understanding of the role's responsibilities. Mention your experience with CI/CD pipelines and model operationalisation, as these are crucial for the position.
Showcase Relevant Projects: If you have worked on projects that involved machine learning pipelines, model monitoring, or data analysis, be sure to include these in your application. Provide specific examples of how you contributed to the success of these projects.
Highlight Soft Skills: In addition to technical skills, emphasise your communication and collaboration abilities. The role requires working closely with Data Scientists and other teams, so showcasing your teamwork and adaptability will strengthen your application.
How to prepare for a job interview at Qualient Technology Solutions UK Limited
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks like Python, R, and MATLAB. Highlight specific projects where you've implemented CI/CD pipelines or worked on model operationalisation, as this will demonstrate your hands-on expertise.
✨Understand the Business Context
Since the role involves working within the banking and financial industry, brush up on relevant practices and regulations. Being able to relate your technical skills to business outcomes will impress the interviewers.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would handle data drift or model performance degradation, and be ready to explain your thought process clearly.
✨Emphasise Collaboration and Communication
This role requires collaboration with Data Scientists and other teams. Be ready to share examples of how you've successfully worked in a team environment, especially in Agile settings, to deliver high-quality results.
