[Remote] Lead Machine Learning Engineer at Williams

United Kingdom

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£97,500 – £97,500Compensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Financial Services, Legal, Professional ServicesIndustries

Requirements

Expertise in data modelling, data quality management, report design, environment management, and automated data ingestion/refresh
Ability to thrive in a global, fast-paced environment as a self-starter and individual contributor
Experience operating within an Agile/Scrum framework
Hands-on technical expertise as a technologist driving best practices
Experience leading a small, distributed team of engineers across multiple regions (US, UK, India)
Proficiency in managing cloud-based platforms, including auto-scaling, Infrastructure as Code, and continuous delivery methodologies
Strong skills in designing, developing, and deploying ML models, algorithms, and agentic AI systems
Expertise in AWS cloud services, particularly Amazon SageMaker, and MLOps
Experience developing and maintaining end-to-end CI/CD pipelines for ML projects using tools like AWS CloudFormation and Terraform
Ability to oversee the ML lifecycle from data preparation to deployment, including high-level design decisions on model architecture and data pipelines
Mentoring skills for junior engineers and collaboration with data scientists, ML engineers, and software teams
Strong client and stakeholder collaboration skills, including gathering requirements, presenting to non-technical audiences, and refining solutions based on feedback
Knowledge of quality, performance standards, monitoring, logging, model improvement, data security best practices, and compliance (e.g., data privacy and confidentiality)

Responsibilities

Maintain and expand the enterprise data model
Develop, publish, and maintain business-critical reports for internal and external stakeholders
Collaborate with Data & Analytics team, business stakeholders, and subject matter experts to solve challenges through reporting, analysis, and data visualization
Provide enterprise-wide expertise in data modelling, data quality management, report design, environment management, and automated data ingestion/refresh
Act as a creative problem-solver contributing to the full product lifecycle and maintaining an organized, scalable reporting environment
Produce reports that inform high-level decision-making and drive revenue growth
Lead a small, distributed team of engineers, ensuring alignment with business goals and service delivery
Manage cloud-based platforms to optimize performance and accelerate delivery
Design, develop, and deploy ML models, algorithms, and agentic AI systems for complex business challenges
Lead implementation of ML solutions on AWS (using SageMaker and related services)
Develop and maintain end-to-end CI/CD pipelines for ML projects using IaC tools like CloudFormation and Terraform
Oversee ML lifecycle: data preparation, model training, validation, and deployment; make high-level design decisions
Mentor junior engineers and collaborate with cross-functional teams for project delivery
Collaborate with project managers and stakeholders to gather requirements, translate business needs, present results, and refine solutions
Ensure ML solutions meet quality/performance standards, implement monitoring/logging, improve model accuracy/efficiency
Enforce data security best practices and compliance with regulations (e.g., data privacy)