Lyrise.ai is revolutionizing tech talent acquisition through AI-driven solutions. We believe in harnessing state-of-the-art machine learning to transform how companies discover and engage top-tier professionals across Europe. Our culture is rooted in innovation, collaboration, and continuous learning, with a focus on delivering cutting-edge products that shape the future of recruitment.
We are seeking a talented and motivated Machine Learning Engineer to join our team in the UK. You will play a pivotal role in building and optimizing models that power our AI-driven recruitment platform. If you’re passionate about applying machine learning techniques to real-world problems, developing scalable systems, and driving impactful results, we’d love to hear from you.
Key Responsibilities
- Design, develop, and implement machine learning models and algorithms to solve complex problems.
- Preprocess and analyze large datasets to extract insights and prepare data for machine learning pipelines.
- Optimize and deploy machine learning models into production systems, ensuring scalability, reliability, and performance.
- Collaborate with cross-functional teams (data scientists, engineers, product managers) to integrate ML solutions into existing products and workflows.
- Continuously monitor and improve model performance by incorporating feedback, retraining models, and enhancing data pipelines.
- Stay updated with the latest advancements in machine learning and AI to ensure the adoption of cutting-edge techniques.
- Document methodologies, processes, and tools to maintain transparency and reproducibility.
- Familiarity with MLOps practices and tools such as MLflow, Kubeflow, or TFX.
- Experience with natural language processing (NLP), computer vision, or time-series analysis.
- Knowledge of containerization and orchestration tools like Docker and Kubernetes.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
- Proven experience (2+ years) in developing and deploying machine learning models.
- Proficiency in Python, with experience in frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Expertise in working with large datasets using SQL and data manipulation libraries like Pandas and NumPy.
- Experience with AWS, Azure, or GCP for deploying machine learning models and managing infrastructure.
- Proficient in Git for collaboration and version control.
- Competitive salary and performance-based bonuses.
- Flexible working arrangements (hybrid and remote options).
- Generous annual leave and holiday policies.
- Opportunities for professional development and certifications.
- Inclusive and collaborative work culture.
- Access to cutting-edge technology and tools.
