Senior Machine Learning Scientist

Hackajob Ltd; Leeds; On-site; GBP 61,000 - 101,000; Full time

Job summary

HSBC is seeking a Senior Machine Learning Scientist via Hackajob to design, deploy, and operate secure AI services at scale. You will own production ML/GenAI pipelines, implement observability, and collaborate with data scientists, engineers, and governance teams to ensure compliant, reliable delivery.

You will work with modern Python ML ecosystems (PyTorch, TensorFlow) and containerized infra (Docker, Kubernetes), building reusable assets and robust CI/CD for ML.

Qualifications

• End-to-end production services ownership with run/support responsibilities.
• Proficiency in Python and modern engineering practices (clean code, testing, packaging, dependency management, Git workflows).
• Hands-on AI deployment patterns and infrastructure (Docker, Kubernetes, API-based serving, batch/stream inference).
• Strong MLOps experience: CI/CD for ML, packaging, release management, automated validation, monitoring, lifecycle management.
• Experience with ML/DL frameworks (PyTorch, TensorFlow) and Python ecosystem for collaboration with data scientists.
• Experience with complex, multi-layered datasets including imbalanced data; data pipelines integration into AI services.
• Building and deploying web APIs using Flask or FastAPI.
• Proficiency with SQL Server or PostgreSQL.
• Strong stakeholder communication; explain technical designs, risks, and operations.
• Good organizational skills and delivery discipline across multiple initiatives.
• Masters preferred; degree in a relevant field.
• Model explainability tools (e.g., SHAP) where governance requires.

Responsibilities

• Design, build, deploy, and operate production-grade AI services (ML/GenAI) that are secure and scalable.
• Operationalise PoC/PoV into hardened solutions with defined non-functional requirements and ownership.
• Develop and maintain MLOps/LLMOps pipelines including CI/CD, testing, packaging, promotion and rollback.
• Create reusable assets (libraries, templates, reference architectures, IaC) to reduce technical debt.
• Implement observability: logging, metrics, tracing, model performance monitoring, drift checks, actionable alerts.
• Partner with data scientists, engineers, and governance stakeholders to meet control and documentation needs.
• Translate business requirements into technical designs and communicate trade-offs clearly.
• Contribute to engineering standards and uplift team capability through coaching.

Skills

Python

ML/DL frameworks

MLOps

Docker

Kubernetes

FastAPI/Flask

Git workflows

Data pipelines

Education

Master's degree

Bachelor's degree

Tools

Docker

Kubernetes

FastAPI

Flask

PyTorch

TensorFlow

SQL/PostgreSQL/SQL Server

Job description

Salary: £61,000 - 101,000 per year

Requirements:

• Strong software engineering experience delivering end-to-end services in production, with ownership for run/support considerations
• Proficiency in Python and modern engineering practices, including clean code, testing, packaging, dependency management, and Git-based workflows
• Hands-on experience with AI deployment patterns and infrastructure, such as Docker, Kubernetes, API-based serving, and batch/stream inference
• Practical MLOps experience, including CI/CD for ML, model packaging and release management, automated validation, monitoring, and lifecycle management
• Working knowledge of ML/DL frameworks and tooling, such as PyTorch, TensorFlow, and the Python ML ecosystem, to collaborate effectively with data scientists and implement inference pipelines
• Experience working with complex, multi-layered datasets, including imbalanced data, and integrating data pipelines into AI services
• Hands-on experience building and deploying web APIs using libraries such as Flask or FastAPI
• Proficiency with database technologies such as SQL Server or Postgres
• Strong stakeholder communication skills, with the ability to explain technical designs, risks, and operational considerations to technical and non-technical audiences
• Good organisational skills and delivery discipline, including prioritisation, time management, and working across multiple initiatives
• Degree in a relevant field or equivalent practical experience, with a Masters preferred
• Model explainability approaches or tools, such as SHAP, where required by the use case and governance expectations

Responsibilities:

• Design, build, deploy, and operate production-grade AI services, including ML and/or GenAI, that are secure, scalable, and reusable across Wholesale use cases
• Productionise PoC and PoV work into hardened solutions with clear non-functional requirements, including performance, resilience, cost, and security, and defined service ownership
• Build and maintain MLOps and LLMOps pipelines, including CI/CD, automated testing, packaging, promotion and rollback, and model/version management, to enable repeatable releases
• Develop reusable engineering assets, such as libraries, templates, reference architectures, and infrastructure-as-code patterns, to reduce technical debt and accelerate delivery
• Implement observability for AI services, including logging, metrics, tracing, model performance monitoring, and quality or drift checks with actionable alerting
• Partner with data scientists, data engineers, platform teams, and governance or risk stakeholders to ensure end-to-end delivery meets control, auditability, and documentation expectations
• Translate business requirements into technical designs and communicate trade-offs and recommendations clearly to technical and non-technical stakeholders
• Contribute to engineering standards and ways of working, including code reviews, design reviews, and documentation, and help uplift team capability through practical coaching

Technologies:

• AI
• API
• CI/CD
• Docker
• FastAPI
• Flask
• Git
• Support
• Kubernetes
• Machine Learning
• MLOps
• Network
• PyTorch
• Python
• SQL
• Security
• TensorFlow
• Web

More:

We are partnering directly with HSBC to hire a Senior Machine Learning Scientist. HSBC is one of the largest banking and financial services organisations in the world, with a network covering more than 50 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and helping people fulfil their hopes and realise their ambitions. We offer opportunities, support, and rewards that can help you go further in your career. We are committed to diverse and inclusive workplaces and to removing barriers so careers are accessible for everyone. We also support disability inclusion and will offer an interview to candidates with disabilities, long-term conditions, or neurodivergent candidates who meet the minimum criteria for the role.

last updated 40 week of 2026