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For Companies At a Glance
- Tasks: Join our team to build and prototype cutting-edge AI technologies for real-world applications.
- Company: AVEVA, a global leader in industrial software with a focus on innovation.
- Benefits: Flexible benefits, 28 days annual leave, private medical insurance, and education assistance.
- Why this job: Make a tangible impact by turning AI research into practical solutions that solve big problems.
- Qualifications: 8+ years in applied AI/ML engineering and strong Python skills required.
- Other info: Collaborative environment with opportunities for career growth and development.
The predicted salary is between 48000 - 72000 £ per year.
AVEVA is creating software trusted by over 90% of leading industrial companies.
We are seeking a Senior AI Research Engineer to join our AI Investigation and Incubation team. This is a hands-on engineering role, focused on building, prototyping, validating, and operationalising emerging AI technologies for real-world industrial intelligence use cases. This role is not a pure academic research position. We are looking for engineers who turn AI research into working systems, make architectural trade-offs, and prove feasibility through code, experiments, and deployable prototypes. The ideal candidate is an ML Research Engineer or Senior Data Scientist with strong practical instincts who thrives at the intersection of experimentation and production.
Key Responsibilities
- Research and evaluate emerging AI technologies with a clear focus on practical applicability and deployability
- Design, build, and iterate on working prototypes and proof-of-concepts
- Develop, fine-tune, evaluate, and benchmark AI/ML models using real-world datasets
- Assess AI approaches for scalability, reliability, cost, security, and operational feasibility
- Make and document engineering and architectural decisions related to model deployment and integration
- Collaborate with software engineers, architects, and platform teams to ensure AI solutions can transition into pilots and downstream products
- Clearly document findings and present actionable recommendations to technical and business stakeholders
- Support early-stage pilots and proof-of-value initiatives where AI solutions are exercised in realistic environments
Essential Requirements
- Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
- 8+ years experience in applied AI/ML engineering, data science, or ML research with production exposure
- 3+ years of hands-on experience building, training, evaluating, and deploying ML models
- Strong proficiency in Python and modern ML frameworks (e.g. PyTorch, TensorFlow, HuggingFace)
- Solid understanding of AI/ML deployment patterns, including:
- Batch and real-time inference
- Model APIs and pipelines
- Integration into distributed systems
- Foundation models / LLMs
- Agent-based systems and orchestration
- Context retrieval and augmentation techniques
Desirable Experience
- Experience deploying ML models in cloud environments (Azure preferred, AWS acceptable)
- Familiarity with MLOps practices (model versioning, evaluation, monitoring, iteration)
- Experience working with non-ideal, real-world data rather than curated research datasets
- Exposure to industrial, IoT, manufacturing, energy, or asset-intensive domains
What Success Looks Like
- AI ideas progress beyond research into validated, working prototypes
- Technical investigations result in clear go / no-go recommendations
- Prototypes demonstrate feasibility for real-world deployment, not just benchmark performance
- Strong collaboration with engineering teams to enable transition into pilots or platforms
- Tangible influence on AI roadmap and technology direction through evidence-backed engineering work
R&D at AVEVA
Our global team of 2000+ developers work on a diverse portfolio of over 75 industrial automation and engineering products, covering data management to 3D design. AI and cloud are at the centre of our strategy, and we have over 150 patents. We value learning, collaboration, and inclusivity. If you want to build applications that solve big problems, join us.
UK Benefits
- Flexible benefits fund, emergency leave days, adoption leave, 28 days annual leave (plus bank holidays), pension, life cover, private medical insurance, parental leave, education assistance program. Benefits may vary by country; primary location benefits apply where relevant.
Hybrid Working
By default, employees are expected to be in their local AVEVA office three days a week, but some positions are fully office-based. Roles supporting particular customers or markets may be remote.
Hiring Process
Interested? Submit your cover letter and CV through our application portal. AVEVA is committed to recruiting and retaining people with disabilities. Please let us know in advance if you need reasonable support during the application process.
About AVEVA
AVEVA is a global leader in industrial software with more than 6,500 employees in over 40 countries. Our solutions are used by thousands of enterprises to deliver essential services safely, efficiently, and more sustainably. We are committed to sustainability and inclusion.
Senior AI Research Engineer in Cambridge employer: AVEVA
Contact Detail:
AVEVA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Research Engineer in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, prototypes, and any real-world applications you've worked on. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at AVEVA.
We think you need these skills to ace Senior AI Research Engineer in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI/ML engineering and showcases your hands-on projects. We want to see how you've turned research into real-world applications, so don't hold back on the details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your skills align with our needs. We love seeing enthusiasm and a clear connection to the role.
Showcase Your Technical Skills: Be specific about your proficiency in Python and any ML frameworks you've used. Mention any cloud deployment experience you have, especially with Azure, as this will catch our eye!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your materials and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at AVEVA
✨Know Your AI Stuff
Make sure you brush up on the latest AI technologies and frameworks, especially those mentioned in the job description like PyTorch and TensorFlow. Be ready to discuss your hands-on experience with these tools and how you've applied them in real-world scenarios.
✨Showcase Your Prototypes
Prepare to talk about any prototypes or proof-of-concept projects you've worked on. Highlight the challenges you faced, the decisions you made regarding architecture, and how you validated your solutions. This will demonstrate your practical instincts and ability to turn research into working systems.
✨Collaboration is Key
Since this role involves working closely with software engineers and architects, be ready to discuss your experience collaborating with cross-functional teams. Share examples of how you’ve successfully transitioned AI solutions into production and the impact it had on the project.
✨Be Ready for Real-World Scenarios
Expect questions that assess your ability to handle non-ideal, real-world data. Prepare examples of how you've dealt with challenges in deploying ML models in cloud environments, particularly Azure, and how you ensured scalability and reliability in your solutions.
