Senior MLOps Engineer deploying ML - powered applications at Allica Bank. Building, prototyping, and ensuring the reliability of AI tools for SMEs.
About the role
- Senior Machine Learning Engineer designing AI systems for multi-scale physical technologies at Orbital. Leading high-risk projects with a focus on AI research and engineering excellence.
Responsibilities
- Define the technical direction for AI systems powering the multi-scale design of physical technologies
- Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices across multiple teams, through hands-on coding, technical review and architectural leadership
- Design robust, well-engineered systems that set the standard for the organisation, balancing research velocity with production requirements
- Drive and influence technical decisions on model selection, training approaches and deployment strategies across the company’s ML efforts, articulating trade-offs to both technical and non-technical stakeholders
- Take ownership of ambiguous, high-risk, cross-functional projects, driving them from inception to completion and coordinating across multiple teams and domains
- Develop and deploy AI solutions across the entire technology development pipeline- computational chemistry simulations, agentic workflows and beyond with responsibility for end-to-end project outcomes
- Rapidly upskill in new technical areas through close collaboration with domain experts, and enable others to do the same (no prior chemistry or materials experience required)
- Perform sophisticated analysis and interpretation of complex datasets, communicating insights and their implications to influence organisational direction
- Design and implement novel ML architectures for complex scientific domains, with work that meets publication standards at top-tier conferences and defines new research directions for the team
- Stay current with state-of-the-art research and contribute to research discussions, providing insights on new developments that influence the team’s research agenda
- Drive research projects from conception through to deployment, showing initiative, technical depth and the ability to make judgment calls on high-uncertainty problems
Requirements
- Extensive AI/ML research and software engineering experience, with a track record of leading complex projects and influencing technical direction — demonstrated through sustained research contributions, senior industry roles, or a combination of both
- Proven track record of leading and delivering high-impact, ambiguous ML/AI projects at scale, with deep understanding of the full ML lifecycle from research to deployment
- Strong engineering fundamentals with the ability to write high-quality, maintainable code and architect robust systems that set organisational standards
- A strong ability to reason about algorithms, system design, linear algebra, probabilistic concepts and ML engineering trade-offs — and to communicate these effectively to influence technical direction
- An ability to debug complex machine learning systems through meticulous attention to detail, testing of edge cases and carefully selected ablations
- Demonstrated ability to mentor and develop engineers, with evidence of shaping others’ technical growth and career trajectories
- A genuine interest in building AI systems that enable breakthrough scientific and industrial applications
- Bonus: Experience with physics-informed or chemistry-focused AI applications. Experience building or fine-tuning large language models. Experience with agent-based systems, tool use or agentic workflows. Contributions to open-source ML projects or published research. Experience influencing technical strategy at an organisational level.
Benefits
- Orbital is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Location requirements
Intermediate AI/ML Engineer designing and deploying machine learning solutions for video security. Join Solink to transform video security into real - time operational insights in a hybrid work environment.
Senior Machine Learning Engineer for Toyota Connected developing state - of - the - art solutions for in - vehicle Voice Assistants. Collaborating with teams and mentoring junior members to drive innovation in machine learning technology.
MLOps Engineer leading large - scale model deployments and managing CI/CD pipelines in GCP ecosystem. Focus on operational excellence and implementing observability frameworks for AI systems.
Machine Learning Engineer at Auror, using data science to reduce retail crime through innovative ML systems. Collaborate with product teams and develop impactful solutions leveraging real - time data.
Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
Machine Learning Engineer designing and implementing AI systems focused on Japanese language challenges at Woven by Toyota. Involves technical R&D, system design, and collaboration with cross - functional teams.
Principal Software Engineer leading MLOps within Analytics Platform at Sun Life. Focused on AWS and machine learning operations, collaborating across technical and business teams.
Machine Learning Engineer designing and optimizing deep learning models for safety - critical environments at Destinus. Shaping the future of high - speed, autonomous flight technologies.
Machine Learning Engineer optimizing personalization systems for Spotify's audio streaming service. Collaborating with cross - functional teams to enhance user experience and deliver recommendations.