We are an innovative company bringing the rigour of inter-disciplinary research to solve complex societal problems. Our projects help users make decisions when tackling complex social challenges such as protecting civilians during crisis, preventing child exploitation and modern slavery. If these are the kinds of challenges you find inspiring, and you have a passion for solving problems that make a real and positive impact in the world, come talk to us.
As a Machine Learning Operations Engineer, you will join the Sociotech for Good business unit in providing ethical AI solutions to customers in the public and private sector. Within this role you will support the advancement of our CESIUM and STRIAD applications, ensuring the development of ML models in a scalable and robust way for production. You will optimise the models developed from a coding and cloud infrastructure side and deploy these into production. You will also support DevOps and system infrastructure as required and contribute to the Data Engineering tribe.
Production-ready Machine Learning via ML Ops & DevOps Support
- Analysing and optimizing machine learning codebases to improve training and inference performance
- Managing the production lifecycle of ML models from initial deployment, to testing and updating of the next iteration.
- Building and maintaining common libraries and frameworks relied upon by the data science team to train, evaluate and deploy models.
- Continue to improve the data pipeline
- Collaborate with the data science team as required.
- Participate in planning efforts, estimation, and peer code-reviews, ensuring high-quality code standards and test-covered development
- Continuously work to improve systems' efficiency and maintainability, reducing technical debt and following best practices
- Support operational delivery and maintenance of products and projects as required.
Coding & documentation
- Write high quality, maintainable code.
- Participate in and support peer-code review process
- Provide clear and useful technical documentation, with details around risks and potential mitigation actions, to the correct standards.
Team support and development
- Support internal training and the development of engineering expertise across the company via participation in the data engineering tribe.
- Where agreed, provide mentorship and/or coaching to more junior team members particularly in skills development.
- Strong organizational, verbal, and written communication and collaboration skills
- Willingness to learn, knowledge share, and improve
- Ability to build credible relationships and influence others
- Ability to display a solution and customer focused mindset
General Knowledge and Technical Skills:
- Strong experience writing production level code in Python.
- Experience with AWS: EC2, EKS, Lambda, S3, SageMaker, ECS.
- Experience working with containerized applications (Docker / Kubernetes)
- Hands-on experience with MLOps tools, such as: Kubeflow, MLFLow.
- Strong experience with Architecture as code: Terraform, CloudFormation.
- Ability to set priorities, focus and to take ownership and drive a task to conclusion without supervision.
- Demonstrable experience in working on collaborative software projects and knowledge of clean software architecture principles
- Experience with technical documentation writing to industry standard.
- Baseline knowledge of engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
- Ability and willingness to discover, evaluate, use, and learn new technologies.
- Experienced working following agile framework and scrum methods
Required Education and Experience:
- 2+ years’ experience ML Ops Engineering in a SaaS environment.
- Masters in computer science, engineering or related subject.
Location: This position is open to candidates based both in and outside of the UK
Contract type: Permanent, full-time Employment Contract
Salary: Commensurate with experience
Hours: Full time
In return, you get ...
- Flexible working hours
- Competitive pension scheme
- Remote working/working from home options
- A friendly and enthusiastic team of experts in the field
To Apply: Please submit both your CV and a cover letter, linking your experience to our requirements in order to have your application considered. References will be required prior to appointment.
We are an Equal Opportunities employer and positively encourage applications from suitably qualified and eligible candidates, regardless of their age, sex, race, disability, sexual orientation, gender reassignment, religion or belief, marital/civil partnership status, or pregnancy and maternity. We are a Disability Confident committed and Living Wage employer.
At Trilateral Research, we value privacy and data protection rights. We have a longstanding data protection culture and promote robust ethical standards in data management and research ethics. Please read our Recruitment Privacy Notice in relation to our recruitment activities before submitting your application to work with us.