At a Glance
- Tasks: Join our team to develop and maintain AI services for smarter shopping experiences.
- Company: Bazaarvoice connects brands and consumers through innovative technology and user-generated content.
- Benefits: Enjoy a collaborative culture, remote work options, and a commitment to diversity and inclusion.
- Other info: Candidates will undergo a Basic level DBS background check.
- Why this job: Be part of a mission-driven company that values innovation, transparency, and customer success.
- Qualifications: Strong Python skills and experience with AWS; familiarity with ML and NLP is a plus.
The predicted salary is between 36000 - 60000 £ per year.
Core Responsibilities:
- Develop and enhance AI services including AI Insights pilot and AI Automated Answers using LLM/RAG architectures.
- Maintain and optimize our mission-critical Machine Moderation system using Python-based NLP models deployed on AWS (Lambda, ECS, SageMaker, SQS, SNS).
- Train, evaluate, and monitor machine learning models using orchestration tools (e.g. Flyte, Airflow).
- Manage ML pipelines on AWS with containerized services and CI/CD deployment via GitHub Actions.
- Implement streaming data processing using Kafka for real-time content moderation decisions.
- Monitor model performance and drift using observability tools (e.g. Arize AI).
- Collaborate with teams using Scala-based services and maintain API integrations for model serving.
- Conduct architectural reviews for ML pipeline design and Infrastructure as Code (Terraform).
- Research and implement novel LLM & NLP approaches for content moderation and consumer insights.
- Optimize batch and streaming ML workloads processing millions of reviews, questions, and answers daily.
Technical Requirements:
- Strong Python proficiency for ML model development and deployment.
- Experience with AWS cloud services (Lambda, ECS, ECR, SageMaker, MSK, SNS, SQS).
- Familiarity with ML orchestration platforms and CI/CD pipelines.
- Knowledge of streaming technologies (Kafka) and high-volume data processing.
- Experience with NLP, LLMs, and production ML monitoring tools.
- Ideally with strong a Software Engineering or Computer Science background.
- Willingness to work with Scala-based systems and learn as needed.
Key Technical Areas:
- Production ML system maintenance using cloud-native AWS infrastructure.
- Real-time and batch model serving with monitoring and alerting.
- Cross-functional API development and integration with existing services.
- Research and development of NLP applications for e-commerce content analysis.
Machine Learning Engineer in Belfast employer: Bazaarvoice
Bazaarvoice is an exceptional employer that fosters a dynamic and innovative work culture, perfect for high-performing individuals eager to make an impact in the EMEA market. With a strong focus on employee growth and development, we offer comprehensive training and mentorship opportunities, ensuring you thrive in your role as a Strategic Retail Account Executive. Located in the UK, our team enjoys a collaborative environment that encourages creativity and strategic thinking, making it an ideal place for those looking to excel in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in Belfast
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as AWS services and Python for ML model development. Having hands-on experience or projects that showcase your skills in these areas can set you apart.
✨Tip Number 2
Engage with the Machine Learning community online. Participate in forums, attend webinars, or contribute to open-source projects related to NLP and ML. This not only enhances your knowledge but also helps you network with professionals in the field.
✨Tip Number 3
Prepare to discuss real-world applications of ML in e-commerce during your interview. Think about how AI can improve customer experiences and be ready to share your insights on innovative solutions that could benefit Bazaarvoice.
✨Tip Number 4
Showcase your collaborative skills by highlighting any past experiences where you worked cross-functionally. Bazaarvoice values teamwork, so demonstrating your ability to work well with others will be crucial in your application.
We think you need these skills to ace Machine Learning Engineer in Belfast
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in machine learning, Python, and AWS. Use keywords from the job description to demonstrate that you meet the technical requirements.
Craft a Compelling Cover Letter:In your cover letter, express your passion for machine learning and how your skills align with Bazaarvoice's mission. Mention specific projects or experiences that showcase your ability to develop and maintain AI services.
Showcase Your Technical Skills:Include specific examples of your experience with ML orchestration platforms, CI/CD pipelines, and streaming technologies like Kafka. This will help illustrate your hands-on expertise in the areas they are looking for.
Highlight Collaborative Experience:Bazaarvoice values teamwork, so mention any collaborative projects you've worked on, especially those involving cross-functional teams or API development. This shows you can work well in their environment.
How to prepare for a job interview at Bazaarvoice
✨Showcase Your Python Skills
As a Machine Learning Engineer, strong Python proficiency is crucial. Be prepared to discuss your experience with Python in detail, including specific projects where you've developed or deployed ML models.
✨Familiarise Yourself with AWS Services
Since the role involves maintaining ML systems on AWS, make sure you understand the key services mentioned in the job description, such as Lambda, ECS, and SageMaker. Be ready to explain how you've used these services in past projects.
✨Demonstrate Your Knowledge of NLP and LLMs
The position requires familiarity with Natural Language Processing and Large Language Models. Prepare examples of how you've applied these technologies in real-world scenarios, particularly in content moderation or consumer insights.
✨Prepare for Technical Questions on ML Pipelines
Expect questions about managing ML pipelines and CI/CD deployment. Brush up on your knowledge of orchestration tools like Flyte or Airflow, and be ready to discuss how you've implemented these in your previous roles.
