Who They Are:

Join a forward-thinking company that helps organisations navigate the complexities of digital communication and mitigate risks before they escalate. Serving a diverse range of clients in highly regulated industries, they provide innovative solutions across more than 80 communication channels to safeguard against compliance, legal, and reputational threats.

This company has been recognised as a leader in their field by industry analysts and has seen impressive growth, consistently ranking among the fastest-growing companies in the U.S. for over a decade. With a commitment to staying at the forefront of innovation, they’re now looking for top talent to continue driving their success.

As a Lead Machine Learning Engineer, you'll take the lead in developing cutting-edge analytics that help unlock valuable insights in the world of communications. Your work will play a key role in shaping their FinTech and RegTech products. You'll collaborate with a talented, cross-functional team—working closely with product managers, data scientists, and other stakeholders—to create secure, resilient, and high-quality SaaS solutions. This role offers a great opportunity to drive innovation and make a real impact in an agile, fast-paced environment.

What you'll need:

• Expertise in JVM languages (Java/Kotlin), Scala, Groovy
• Background in Natural Language Processing (NLP), ML-Ops, and data pipeline development
• Proficient with machine learning frameworks and libraries, including TensorFlow, PyTorch, and scikit-learn
• Deep knowledge of machine learning algorithms, statistical methods, and data analysis techniques
• Skilled in data processing, feature engineering, and model evaluation practices
• Familiarity with cloud platforms such as Amazon Web Services (AWS) and Google Cloud
• Hands-on experience with Amazon SageMaker and Jupyter Notebooks
• Knowledge of model serving technologies, including Triton Inference Server
• Experience developing AI/ML-driven analytics products in Fintech/Regtech
• Expertise in microservices and event-driven architecture
• Knowledge of building scalable ML applications and services in cloud environments
• Experience with messaging systems like Kafka and relational databases such as MySQL and Postgres
• Proficient in working with containerized platforms such as Docker, Helm, and Kubernetes
• Experience with CI/CD tools, including Bamboo and Argo CD
• Skilled in monitoring tools like Prometheus and Grafana
• Strong proficiency in API design and development
• Experienced in working with distributed systems

Find out more

If you would like to have a confidential conversation and find out more about this opportunity, then get in touch with at Johnathan Potts Search 5.0 on or click apply