At a Glance
- Tasks: Create innovative AI solutions using NVIDIA technologies in fast-paced environments.
- Company: Leading AI consultancy with a global presence and a focus on high-impact projects.
- Benefits: Competitive daily rate, flexible contract duration, and the chance to work on transformative projects.
- Other info: Opportunity to work in high-governance sectors like Pharma and Fintech.
- Why this job: Join a team at the forefront of AI innovation and make a real difference across industries.
- Qualifications: Experience with NVIDIA tools, strong Python skills, and a knack for rapid prototyping.
The predicted salary is between 80000 - 100000 £ per year.
Urgent Contract Senior AI Engineer – NVIDIA Specialisation (£##########0/day). Our client, a leading AI consultancy with operations across the UK, US, UAE and EU, is seeking exceptional engineers for a rapid prototyping engagement across four high-impact domains: Pharma, Fintech, Banking, and FMCG. You'll work directly with cutting-edge AI infrastructure and agentic systems, translating complex requirements into production-ready solutions within tight timeframes. This is ideal if you thrive at the intersection of innovation and delivery in regulated, high-governance environments.
What we're looking for:
- Hands-on experience with NVIDIA's ecosystem: LLM inference and optimisation (TensorRT-LLM, Triton, NIM)
- Agentic AI frameworks (NeMo, AgentIQ, NeMo Guardrails)
- Foundational models and RAG architectures
- Data acceleration (cuDF, RAPIDS)
- Multimodal or spatial AI (Cosmos, cuOpt, Metropolis)
- Strong Python development, Docker/Kubernetes, Azure familiarity, and the ability to ship POCs and technical artifacts rapidly
The role:
- Contract basis, 3-6 months initial
- Work across Pharma, Fintech, Banking, and FMCG transformations
- High-governance, compliance-focused environments
Senior AI Engineer (NVIDIA specialist) employer: Nvidia
Join a leading AI consultancy that champions innovation and excellence, offering you the chance to work on transformative projects across high-impact sectors like Pharma, Fintech, Banking, and FMCG. With a strong focus on employee growth, you'll have access to cutting-edge technology and a collaborative work culture that values your expertise in NVIDIA's ecosystem. This role not only promises competitive remuneration but also the opportunity to make a significant impact in regulated environments, making it an ideal choice for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer (NVIDIA specialist)
✨Showcase Your Skills with a Public Portfolio
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We think you need these skills to ace Senior AI Engineer (NVIDIA specialist)
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Senior AI Engineer (NVIDIA specialist) at Nvidia, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at Nvidia.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at Nvidia
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
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When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
