Principal Machine Learning Engineer

Principal Machine Learning Engineer

Permanent, Full-Time

Westhill, Aberdeen with Hybrid working

The Principal Machine Learning Engineer will join a cutting-edge Digital Innovation team at the core of the Energy Division’s technology and efficiency strategy. In this role, you will design and deploy advanced machine learning solutions across complex, real-world environments such as offshore wind, subsea engineering, and large-scale energy infrastructure. This is a unique opportunity to apply state‑of‑the‑art AI at scale, driving operational excellence and shaping the future of data‑driven decision‑making in the energy sector.

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• Lead the end‑to‑end design, development, and deployment of scalable, secure machine learning solutions in production environments.
  
• Define and implement MLOps best practices across the ML lifecycle, including CI/CD, monitoring, automated testing, and model governance.
  
• Architect and optimize ML infrastructure and cloud‑native environments to improve scalability, maintainability, and cost efficiency.
  
• Research, prototype, and productionise advanced ML models for time‑series, streaming, and sensor data, driving measurable performance improvements.
  
• Collaborate with cross‑functional teams to align ML solutions with business objectives, regulatory requirements, and ethical standards.
  
• Mentor and coach junior ML engineers and data scientists, fostering technical excellence and a culture of innovation.
  
• Establish rigorous documentation and monitoring standards to ensure reliability, transparency, and compliance in deployed ML systems.
  
• Engage senior stakeholders, translating complex ML concepts into clear business value and influencing enterprise AI strategy.
  

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• Expertise in Python and key data science libraries (NumPy, Pandas, Scikit‑Learn, PyTorch, TensorFlow) with strong ML/AI knowledge, including deep learning, time‑series modelling, and LLMs (fine‑tuning, RAG).
  
• Hands‑on experience with cloud platforms (AWS, Azure, GCP) and infrastructure tools (Terraform, Kubernetes, Docker), plus software development best practices (testing, version control, CI/CD).
  
• Proven ability to implement MLOps practices and manage the ML lifecycle, including reproducibility, monitoring, automated pipelines, and model governance.
  
• Strong background in distributed computing and real‑time data streaming (Kafka, Spark, Ray) and experience with time‑series/sensor data optimisation.
  
• Excellent communication and stakeholder engagement skills, with ability to translate technical concepts into business outcomes and influence senior leaders.
  
• Demonstrated leadership in mentoring teams, problem‑solving, and delivering measurable business impact in regulated environments.
  

James Fisher is a global engineering services company with over 50 years of experience delivering complex offshore energy projects in some of the world’s most challenging environments. We operate across Energy, Defence, and Maritime Transport, leveraging cutting‑edge technology and deep expertise to support the full lifecycle of our customers’ assets.

In the Energy Division, we provide safe, efficient solutions across oil & gas and renewables - from well support and full‑field decommissioning to integrated services for offshore wind and expert subsea inspection, repair, and maintenance. Our work helps operators extend asset life, reduce downtime, and respond rapidly to operational challenges, driving the global shift toward a cleaner, more sustainable future.

Our One James Fisher strategy unites our capabilities under a single vision, building a stronger, more cohesive business within the Blue Economy.

Due to the volume of applications we receive for our vacancies, on occasion applications may close before the deadline, so please apply early to avoid disappointment.

James Fisher and Sons are committed to taking positive action on diversity and strongly encourage applications for candidates from all backgrounds. We are proud to be a Disability Confident employer and recognise that our success depends on our talented and diverse workforce.