ML/MLOps Research Engineer

Location: Manchester, UK (Hybrid). Ordinarily work three days per week in the central Manchester office and remotely on the remaining days; customer-site work within Manchester may be required up to five days per week.

Salary: £45,000–£80,000 per year, depending on experience and level of appointment, plus equity.

Company

hirify.global is a Manchester-based technology consultancy that researches, prototypes, and productionises machine learning for a diverse range of clients, including secure government customers.

What you will do

• Collaborate with clients, team leads, and customers to understand needs, build relationships, and present solutions through demos, workshops, and training.
• Design and implement high-quality machine learning and software features with strong documentation and automated testing.
• Participate in sprint planning, retrospectives, code reviews, and project delivery planning.
• Work across ML research, production ML, and MLOps while maintaining high engineering standards.
• Contribute to R&D projects, blogs, and videos that share learnings with the MLOps community.

Requirements

• Undergraduate degree in computer science, mathematics, or a similar subject, or a relevant postgraduate degree.
• Active SC clearance at minimum and experience working on secure government projects, ideally in high-side environments.
• Passion for coding, machine learning, and open source technologies, with demonstrable Python programming experience.
• Proven research engineering experience in a secure government context, applying ideas from research literature to concrete customer problems in a repeatable way.
• Knowledge of transformer architecture and experience working with large language models.
• Experience delivering software using an agile development methodology.
• Fluency with Git, Unix/Linux, and Docker.
• Ability to work at pace, adapt to evolving project needs, and proactively engage with customers.

Nice to have

• Awareness of ML security and safety topics, ML model internals, and the broader landscape of machine learning applications, tools, and technologies.
• Strong interest in keeping up with emerging large language models and vector-database text retrieval.

Culture & Benefits

• Hybrid working with three regular office days and remote work on the remaining days.
• 25 days of holiday, rising to 30 days with each year of service.
• Enhanced maternity, paternity, and adoption leave, plus a healthcare cash plan.
• £500 annual personal development budget and an AI assistant of choice.
• Equity option scheme, Cycle to Work Scheme, secure bike storage, paid charity and volunteering leave, and company socials.

Hiring process

• Apply through the company careers page with a few words about yourself and what interests you about the role.
• Include a link to GitHub, Bitbucket, or a similar profile; Kaggle profiles, technical blogs, side projects, or other relevant work may also be provided.