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- Tasks: Build and optimise AI-driven Q&A systems using large language models.
- Company: Join Cognizant, a leader in innovation and collaboration.
- Benefits: Competitive salary, diverse work culture, and opportunities for growth.
- Why this job: Make an impact by developing cutting-edge AI technology that transforms information access.
- Qualifications: Experience in machine learning, NLP, and proficiency in Python required.
- Other info: Dynamic team environment with a focus on creativity and efficiency.
The predicted salary is between 36000 - 60000 £ per year.
Overview
We are looking for a results-oriented AI Engineer to join our team developing intelligent Q&A systems powered by large language models. You will help build, test, and optimize pipelines that enable automatic question-answering from large document collections, supporting our mission to surface key knowledge rapidly and accurately.
Responsibilities
- Build, fine-tune, and evaluate LLM-based Q&A models using frameworks like AWS Bedrock, Langchain, HuggingFace Transformers or OpenAI API.
- Design prompt templates and implement retrieval strategies to increase answer precision and factuality.
- Assist in creating data pipelines for training and testing, including annotation and evaluation tooling.
- Collaborate with senior engineers and product managers to translate user requirements into technical features.
- Participate in error analysis, iterative model improvement, and performance tuning.
- Document code and workflows clearly; follow best practices for reproducibility and code quality.
Requirements
- Hands-on experience with machine learning, NLP, or information retrieval projects, preferably with language models.
- Proficiency in Python and familiarity with deep learning/NLP libraries (Langchain, PyTorch, TensorFlow, HuggingFace Transformers).
- Knowledge of vector databases or semantic search concepts is desirable.
- Experience with Git, collaborative development workflows, and cloud infrastructure (AWS, Azure, GCP, Domino) is a plus.
About Cognizant
At Cognizant you will experience an exciting mix of innovation by design, creativity, collaboration, and efficiency within a framework of stimulating objectives and a passion for delivering the best to our customers.
Our Associates are chosen for their attitude, skills, knowledge, and enthusiasm but above all, their belief that anything is possible.
Equal Opportunity
Cognizant is an equal opportunities employer, and we welcome all applications regardless of race, colour, gender, ethnic origin, nationality, religion or beliefs, disability, age, sexual orientation, political opinions, or trade union membership.
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AI Engineer – Document Q&A (LLM Applications) employer: Cognizant
Contact Detail:
Cognizant Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer – Document Q&A (LLM Applications)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning space, especially those who work with large language models. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to NLP or information retrieval. Whether it’s a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and deep learning libraries. Practice coding challenges and be ready to discuss your past projects in detail—this is your time to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace AI Engineer – Document Q&A (LLM Applications)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Engineer role. Highlight your hands-on experience with machine learning and NLP projects, and don’t forget to mention any relevant frameworks you’ve worked with!
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 background makes you a perfect fit for our team. Be sure to mention specific projects or achievements that relate to the job description.
Showcase Your Technical Skills: When filling out your application, be clear about your proficiency in Python and any deep learning libraries you've used. If you have experience with cloud infrastructure or vector databases, make sure to highlight that too!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Cognizant
✨Know Your Tech
Make sure you brush up on your knowledge of machine learning, NLP, and the specific frameworks mentioned in the job description, like AWS Bedrock and HuggingFace Transformers. Being able to discuss your hands-on experience with these technologies will show that you're not just familiar but also capable.
✨Prepare for Problem-Solving Questions
Expect to tackle some technical challenges during the interview. Practice explaining your thought process when building or optimising Q&A models. This could involve discussing how you would design prompt templates or implement retrieval strategies to enhance answer precision.
✨Showcase Collaboration Skills
Since the role involves working closely with senior engineers and product managers, be ready to share examples of past collaborations. Highlight how you translated user requirements into technical features and how you handled feedback during projects.
✨Document Your Work
Demonstrate your commitment to best practices by discussing how you document code and workflows. Mention any tools or methods you use to ensure reproducibility and code quality, as this is crucial for the role.
