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- Tasks: Join a cutting-edge team to build scalable AI systems and innovate in machine learning.
- Company: Aventis Solutions partners with a fast-growing British tech team focused on AI innovation.
- Benefits: Enjoy a competitive salary, bonuses, pension contributions, private healthcare, and flexible hybrid working.
- Why this job: Be part of an elite innovation team with opportunities for career progression and specialisation.
- Qualifications: Strong background in data science, machine learning, or software engineering; proficiency in Python and ML frameworks.
- Other info: Work in a collaborative environment with a focus on experimentation and real-world impact.
The predicted salary is between 55000 - 100000 £ per year.
Aventis Solutions has partnered with a fast-growing British tech team seeking a series of AI/ML Engineers, including Senior, Principal & Team Leads, to build scalable, production-grade AI systems and help shape a forward-thinking machine learning and engineering capability. This is your opportunity to work in an elite innovation team, surrounded by cutting-edge tools and backed by the resources of a global tech leader. We are looking for a range of AI engineers, so if you have a strong background as a data scientist, a data engineer, or a full-stack software engineer, we would like to hear from you.
Key details:
- Salary: £65,000-£125,000 + 10-40% bonus + 10% pension contribution + private healthcare allowance + strong benefits package
- Location: London HQ + flexible hybrid working model (remote)
Future Outlook: Long-term career progression toward Lead or Staff Engineer, AI/ML Enterprise Architect, or senior leadership positions. As the AI Innovation Lab grows, there will be ample opportunity to specialise in advanced areas such as LLM systems, MLOps, or cloud AI platforms, or to take on broader product or technical leadership roles.
Key Skills, Attributes & Tech Desired:
- Builder: Solid background in building and deploying data science, machine learning or statistical models at scale, ideally within product environments or a data-rich business.
- Tech-savvy: Proficient in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX). Strong command of cloud-native AI tooling (e.g., AWS SageMaker, GCP Vertex AI, AzureML/AzureAI, MLflow, Weights & Biases).
- Well-rounded Engineer: Comfortable working with version-controlled codebases, DevOps pipelines, containerisation/microservices (Docker/Kubernetes), and Infrastructure-as-Code (Terraform).
- Data-driven: Experience working with big data systems like Databricks, Spark, Kafka, Snowflake, or BigQuery. Familiarity with batch and streaming ML pipelines is ideal.
- LLM-curious: Hands-on exposure to LLMs or interest in working on generative AI use cases (e.g., embeddings, retrieval-augmented generation, fine-tuning). Exposure to the likes of LangChain, OpenAI API, Anthropic Claude, Mistral, Groq, Cohere, vLLM or similar is desirable.
- Innovator: Passionate about experimentation and new techniques. You enjoy solving complex problems, building reusable ML components, and staying up to date with frontier AI tools and architecture: agentic AI.
- Collaborative: A great team player who works well with cross-functional colleagues in product, data engineering, and DevOps. You are comfortable pair-programming, reviewing code, and participating in agile ceremonies.
- Commercial: You understand the impact of artificial intelligence and machine learning on real-world outcomes and enjoy shaping systems that make a tangible difference to users or business metrics.
- Communication: Able to clearly explain complex concepts to a range of audiences. Comfortable presenting ideas, sharing research findings, or demoing model performance.
- Regulated Industry Exposure: Background or exposure to domains like banking, insurance, FinTech, energy or asset management is a plus, but it is not required.
Role Overview: AI/ML Engineers: AI Innovation Team: You will help build the technical backbone of this next-generation AI lab, contributing to everything from data pipelines and training infrastructure to the deployment of advanced AI systems and LLM-powered applications. We are looking for any of the following: Data Scientist, Python Engineer, MLOps Engineer, AI Engineer, Machine Learning Engineer, Data Engineer, Full-stack software engineers and similar to become forward-thinking innovators. The team is highly technical, research-oriented, and focused on experimentation. The company is already investing heavily in AI infrastructure, model tooling, and R&D environments. So, you will play a critical role in designing, training, evaluating, and deploying production-ready models while contributing to reusable architecture and automation for future scalability.
Interested? Please submit your CV via LinkedIn or message Billy Hall for further information.
AI/ML Engineer - Senior, Principal & Team Lead - Team Build employer: Aventis Solutions
Contact Detail:
Aventis Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer - Senior, Principal & Team Lead - Team Build
✨Tip Number 1
Familiarise yourself with the latest AI/ML frameworks and tools mentioned in the job description, such as PyTorch, TensorFlow, and cloud-native AI tooling like AWS SageMaker. Being able to discuss your hands-on experience with these technologies during interviews will set you apart.
✨Tip Number 2
Showcase your collaborative skills by preparing examples of how you've worked effectively in cross-functional teams. Highlighting your experience in pair programming or participating in agile ceremonies can demonstrate your ability to fit into their team-oriented culture.
✨Tip Number 3
Stay updated on the latest trends in AI, especially around LLMs and generative AI. Being able to discuss recent advancements or projects you've worked on in this area can show your passion for innovation and experimentation, which is highly valued by the company.
✨Tip Number 4
Prepare to articulate the real-world impact of your previous AI/ML projects. Understanding how your work has influenced business metrics or user outcomes will resonate well with the commercial aspect of the role they are looking to fill.
We think you need these skills to ace AI/ML Engineer - Senior, Principal & Team Lead - Team Build
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI/ML, particularly any work with data science, machine learning models, or software engineering. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and ML. Discuss specific projects you've worked on that demonstrate your ability to build scalable systems and your familiarity with the technologies mentioned in the job description.
Showcase Your Technical Skills: In your application, be sure to detail your proficiency in Python and any ML frameworks you’ve used. Mention your experience with cloud-native AI tools and big data systems, as these are crucial for the role.
Highlight Collaboration Experience: Since the role requires working with cross-functional teams, include examples of how you've successfully collaborated with colleagues in product, data engineering, or DevOps. This will demonstrate your ability to thrive in a team-oriented environment.
How to prepare for a job interview at Aventis Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and modern ML frameworks like PyTorch or TensorFlow. Highlight specific projects where you've built and deployed machine learning models, especially in production environments.
✨Demonstrate Your Problem-Solving Ability
Expect to face technical challenges during the interview. Be ready to explain your thought process when tackling complex problems, and share examples of how you've innovated or experimented with new techniques in AI.
✨Emphasise Collaboration
Since the role requires working closely with cross-functional teams, be sure to illustrate your teamwork skills. Share experiences where you've successfully collaborated with product managers, data engineers, or DevOps teams.
✨Communicate Clearly
You’ll need to explain complex concepts to various audiences. Practice articulating your ideas and findings in a clear and concise manner, as this will be crucial during presentations or discussions about your work.
