At a Glance
- Tasks: Develop and optimise machine learning models using Spark ML for predictive analytics.
- Company: Synechron is a leading tech firm in financial services, driving innovation globally.
- Benefits: Enjoy hybrid working, swift onboarding, strong market rates, and excellent benefits.
- Why this job: Join a collaborative culture focused on empowerment and cutting-edge technology in machine learning.
- Qualifications: Proficiency in Spark ML, Python, and experience with distributed systems like Hadoop required.
- Other info: Diversity and inclusion are core values; all backgrounds are encouraged to apply.
The predicted salary is between 84000 - 126000 £ per year.
Synechron is looking for a skilled Machine Learning Developer with expertise in Spark ML to work with a leading financial organisation on a global programme of work. The role involves predictive modeling, and deploying training and inference pipelines on distributed systems such as Hadoop. The ideal candidate will design, implement, and optimise machine learning solutions for large-scale data processing and predictive analytics.
Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.
Role:
- Develop and implement machine learning models using Spark ML for predictive analytics
- Design and optimise training and inference pipelines for distributed systems (e.g., Hadoop)
- Process and analyse large-scale datasets to extract meaningful insights and features
- Collaborate with data engineers to ensure seamless integration of ML workflows with data pipelines
- Evaluate model performance and fine-tune hyperparameters to improve accuracy and efficiency
- Implement scalable solutions for real-time and batch inference
- Monitor and troubleshoot deployed models to ensure reliability and performance
- Stay updated with advancements in machine learning frameworks and distributed computing technologies
Experience:
- Proficiency in Apache Spark and Spark MLlib for machine learning tasks
- Strong understanding of predictive modeling techniques (e.g., regression, classification, clustering)
- Experience with distributed systems like Hadoop for data storage and processing
- Proficiency in Python, Scala, or Java for ML development
- Familiarity with data preprocessing techniques and feature engineering
- Knowledge of model evaluation metrics and techniques
- Experience with deploying ML models in production environments
Permanent or Contract position – Swift onboarding – Strong market rates – Excellent benefits – Hybrid working (x3 days in office)
Diversity Statement
Synechron are proud to be an equal opportunity employer. Our Diversity, Equity, and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality, diversity and an environment that is respectful to all. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We offer flexible workplace arrangements, mentoring, internal mobility, learning and development programmes to support our global workforce. Empowerment and collaboration are at the core of how we operate.
All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicants gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
Seniority level
- Seniority levelMid-Senior level
Employment type
- Employment typeFull-time
Job function
- Job functionInformation Technology
- IndustriesTechnology, Information and Internet and Financial Services
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Machine Learning Engineer (London) employer: Synechron
Contact Detail:
Synechron Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (London)
✨Tip Number 1
Familiarise yourself with Apache Spark and Spark MLlib. Since the role specifically requires expertise in these technologies, consider working on personal projects or contributing to open-source projects that utilise them. This hands-on experience will not only boost your confidence but also demonstrate your practical skills during interviews.
✨Tip Number 2
Network with professionals in the machine learning field, especially those who work with distributed systems like Hadoop. Attend meetups, webinars, or conferences related to machine learning and data engineering. Building connections can lead to valuable insights and potential referrals for the job.
✨Tip Number 3
Stay updated with the latest advancements in machine learning frameworks and distributed computing technologies. Follow relevant blogs, podcasts, and research papers. Being knowledgeable about current trends will help you stand out in interviews and show your commitment to continuous learning.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design problems related to machine learning. Use platforms like LeetCode or HackerRank to sharpen your skills. Additionally, be ready to discuss your past projects and how you’ve implemented machine learning solutions in real-world scenarios.
We think you need these skills to ace Machine Learning Engineer (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Apache Spark, Spark MLlib, and any relevant predictive modelling techniques. Use specific examples to demonstrate your skills in developing machine learning models and working with distributed systems like Hadoop.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background aligns with the job requirements, particularly your proficiency in Python, Scala, or Java, and your experience with data preprocessing and feature engineering.
Showcase Relevant Projects: If you have worked on projects involving machine learning solutions or large-scale data processing, be sure to include these in your application. Describe your role, the technologies used, and the outcomes achieved to illustrate your capabilities.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops you've attended related to machine learning frameworks or distributed computing technologies. This shows your commitment to staying updated in the field and can set you apart from other candidates.
How to prepare for a job interview at Synechron
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Apache Spark and Spark MLlib. Bring examples of past projects where you've implemented machine learning models, especially those involving predictive analytics and large-scale data processing.
✨Understand the Role Requirements
Familiarise yourself with the specific tasks mentioned in the job description, such as designing training pipelines and collaborating with data engineers. This will help you demonstrate how your experience aligns with their needs.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, particularly in model evaluation and hyperparameter tuning. Be ready to explain your thought process and the techniques you would use to improve model performance.
✨Stay Updated on Industry Trends
Research the latest advancements in machine learning frameworks and distributed computing technologies. Showing that you're proactive about staying current can impress interviewers and demonstrate your commitment to the field.