Machine Learning Engineer

Version 1 has celebrated over 28 years in Technology Services and continues to be trusted by global brands to deliver solutions that drive customer success. Version 1 has several strategic technology partners including Microsoft, AWS, Oracle, Red Hat, OutSystems and Snowflake. We’re also an award-winning employer reflecting how employees are at the heart of Version 1.

We’ve been awarded: Innovation Partner of the Year Winner 2023 Oracle EMEA Partner Awards, Global Microsoft Modernising Applications Partner of the Year Award 2023, AWS Collaboration Partner of the Year - EMEA 2023 and Best Workplaces for Women by Great Place To Work in UK and Ireland 2023.

As a consultancy and service provider, Version 1 is a digital-first environment and we do things differently. We’re focused on our core values; using these we’ve seen significant growth across our practices and our Digital, Data and Cloud team is preparing for the next phase of expansion. This creates new opportunities for driven and skilled individuals to join one of the fastest-growing consultancies globally.

We are looking for a Machine Learning Engineer to operationalize models and build scalable ML systems on AWS for financial applications. This role focuses on production-grade deployment, automation, and lifecycle management of ML solutions.

Key Responsibilities

Production ML Systems:

Convert prototypes into robust, low-latency services for batch and real-time inference.
Design feature stores, training pipelines, and model registries using AWS-native tools.

AWS Architecture & Engineering:

Build ML pipelines leveraging AWS services (SageMaker, Glue, Lambda, Step Functions, Redshift).
Optimize cost, performance, and reliability for production workloads.

Data Engineering & Performance:

Develop PySpark and SQL transformations for large financial datasets.
Ensure data quality and reproducibility across pipelines.

MLOps & Compliance:

Implement CI/CD for ML, model versioning, and automated retraining.
Set up monitoring for drift, performance, and security compliance.

Collaboration & Delivery:

Work closely with Data Scientists and stakeholders to align ML solutions with business goals.
Document architecture, runbooks, and operational guidelines.

Required Skills & Qualifications

5+ years of strong programming skills in Python, PySpark, and SQL.
Hands-on experience with AWS services (SageMaker, Glue, Lambda, Redshift, Step Functions). Expertise in MLOps practices and production deployment of ML models. Familiarity with financial data and compliance requirements.

Preferred Qualifications

Experience with SageMaker Pipelines and Feature Store.
Knowledge of streaming inference and event-driven architectures. AWS certifications (ML Specialty, Solutions Architect) are a plus.

At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their well-being, professional growth, and financial stability.

One of our standout advantages is the ability to work with a hybrid schedule along with business travel, allowing our employees to strike a balance between work and life. We also offer a range of tech-related benefits, including an innovative Tech Scheme to help keep our team members up-to-date with the latest technology.

We prioritise the health and safety of our employees, providing private medical and life insurance coverage, as well as free eye tests and contributions towards glasses. Our team members can also stay ahead of the curve with incentivized certifications and accreditations, including AWS, Microsoft, Oracle, and Red Hat.

Our employee-designed Profit Share scheme divides a portion of our company's profits each quarter amongst employees. We are dedicated to helping our employees reach their full potential, offering Pathways Career Development Quarterly, a programme designed to support professional growth.