Machine Learning & AI Engineer

At Voyc, we’re building solutions to help financial services companies better understand and manage their customer interactions. As we continue to grow, we’re looking for a talented Machine Learning Engineer to join our team and develop features that empower our customers to make informed decisions.

In this role, you’ll work on impactful projects that shape the future of our platform and deliver actionable, data-driven insights. You’ll be part of a team that pushes the boundaries by integrating natural language processing (NLP) and large language models (LLMs) to refine and expand our machine learning systems.

The ideal candidate will bring expertise in machine learning, programming, and automation in real-world applications. This is a unique opportunity to work on cutting-edge technologies, optimise text-based machine learning models, and contribute to a high-impact, fast-growing SaaS platform.

The Role

As an ML & AI Engineer, you will leverage advanced artificial intelligence, machine learning, and data science techniques to support autonomous data-driven decision-making processes and deliver personalised customer experiences across our platform.

You will design, develop, and deploy a range of AI and ML products and features, using LLMs and other analytical and predictive AI solutions. You’ll collaborate with Product, Engineering, and Data Science teams to enhance the platform’s AI capabilities, improve model performance, and build scalable machine learning solutions.

Key Responsibilities

Machine Learning Development

• Design, develop, and deploy ML models and algorithms to solve complex business problems.
• Develop and enhance NLP models for classification, insights extraction, task prioritisation, and recommendation systems.
• Work with structured and unstructured data to analyse trends and develop solutions that improve decision-making and automation.
• Ensure that all AI models and data handling practices comply with relevant laws and ethical guidelines.

Prompt Engineering & Generative AI

• Develop and expand the capabilities of our LLMs and interactive AI assistant, focusing on generative AI applications.
• Refine and optimise LLM output and reliability using prompt engineering techniques.
• Incorporate techniques like Retrieval-Augmented Generation (RAG), vector databases, and semantic searches to improve precision and relevance in data extraction from large datasets.
• Collaborate with Product and stakeholders to define AI use cases and implement effective prompting strategies.

MLOps & AI Infrastructure

• Architect and maintain scalable, containerised environments for AI model deployment.
• Implement and manage CI/CD pipelines for seamless integration and delivery.
• Integrate experiment tracking and monitoring tools to record modelling progress and deployment performance.
• Leverage model optimisation and quantisation frameworks to streamline model inference, reduce latency, and enable efficient scaling of ML deployments.

Collaboration & Innovation

• Must be able to work closely with data scientists, software engineers, and product teams to define requirements and deliver AI-driven solutions.
• Continuously monitor advancements in AI and LLM technologies and review relevant academic literature and industry releases to ensure our strategies and implementations align with the latest innovations and standards.
• Prototype ML systems and AI concepts, particularly those using NLP and LLMs, and evaluate the effects of different models and techniques on AI performance.

Our Tech Stack

• Programming Languages: Python
• ML & Data Science Libraries: pandas, scikit-learn, TensorFlow, PyTorch, HuggingFace
• MLOps & Infrastructure: AWS (EC2, Lambda, S3, EFS, Bedrock), CI/CD (CodePipeline), MLflow, vLLM, ONNX
• Other AI Technologies: Transformers, automatic speech recognition, predictive analytics, ElasticSearch, Kafka
• Monitoring Tools: Prometheus, Grafana (knowledge of / experience with these is beneficial)

Requirements

Must-Have Skills & Experience

• Bachelor Degree in a Science or Engineering discipline.
• At least 2 years of experience in machine learning and generative AI feature development, with expertise in NLP.
• Experience developing and deploying NLP models for text and token classification, sentence similarity, anomaly detection, and text generation.
• An understanding of transformer-based architectures and experience with the HuggingFace ecosystem and AI/ML frameworks (e.g., TensorFlow, PyTorch)
• Strong understanding of MLOps practices, including experiment tracking, model versioning, and cloud-based deployments (AWS preferred).
• Ability to develop innovative and scalable ML/AI solutions that are business-ready.

Bonus Points (advantageous but not required)

• Demonstrated ability to implement ML workflows at scale, particularly using LLMs, in a SaaS or enterprise environment.
• Experience in handling, analysing, and extracting insights from large and complex datasets, particularly noisy text data.
• Previous experience tuning open source and proprietary large language models.
• Prior experience mentoring or leading junior ML engineers.

Benefits

What we offer

• A caring, growth-focused team culture where we support your personal and professional goals.
• Flexible working hours and a forward-thinking approach to leave policies.
• Company-sponsored lunches, travel, and learning opportunities, including an annual all expenses week away team offsite.
• An inclusive and representative workplace that values diversity.
• Competitive salary and equity options, giving you ownership in Voyc’s success.
• A flexible, hybrid or remote working model, so you can choose to work from home or our office.

Join us at Voyc to make a real impact on the financial services industry and grow your career in a supportive and innovative environment!