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For Companies At a Glance
- Tasks: Design and develop cutting-edge AI solutions for a global law firm.
- Company: Join a top-tier global law firm undergoing an exciting cloud transformation.
- Benefits: Competitive salary, collaborative environment, and opportunities for professional growth.
- Why this job: Make a real impact with advanced analytics and innovative AI technologies.
- Qualifications: 2-4 years in AI/ML, knowledge of cloud platforms, and strong coding skills.
- Other info: Dynamic team with diverse projects and excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Job Description
Data Science Engineer – MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL
We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) to join their team on a permanent basis. this role we be responsible for the design, development and delivery of advanced analytics and AI solutions.
This is a fantastic time to join a top-tier global law firm who have a long-stream of projects in the pipeline alongside a diverse and collaborative team environment.
To be considered for this Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have:
- Ideal but not required law firm experience
- 2-4 years experience within AI/ML positions
- Knowledge of cloud platforms (Ideally Azure)
- AI/ML Frameworks
- Generative AI
- Data engineering knowledge
Solution Delivery
- Design, build, and deploy data science and AI solutions end-to-end, from design and development through testing, release, monitoring, and support.
- Operationalize models with CI/CD pipelines, automated testing, and monitoring, applying MLOps practices such as versioning, retraining, and drift detection (tools: MLflow, Azure ML, Databricks)
- Leverage both open-source frameworks (LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to deliver production ready, scalable AI solutions
- Implement generative AI and advanced analytics features, including embeddings, retrieval-augmented generation, and building AI agents and chat-based solutions.
- Write clean, testable, and well-documented code using modern engineering practices (unit testing, code reviews, API development, Azure DevOps preferred).
Technical Design & Architecture
- Ensure solutions align with enterprise architecture, data governance, and security standards
- Collaborate with enterprise architects, IT, and business stakeholders to validate approaches
- Contribute to lifecycle management practices including model versioning, monitoring, and continuous improvement of delivery processes
- Evaluate and pilot emerging technologies to improve scalability and solution quality.
Data Science Engineer employer: Precise Placements
Contact Detail:
Precise Placements Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Engineer
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving MLOps, AI, and cloud platforms like Azure. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data science and machine learning questions. Practice explaining your past projects and how you’ve used tools like TensorFlow and Docker. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Data Science Engineers like you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Science Engineer role. Highlight your experience with MLOps, AI, and any relevant frameworks like PyTorch or TensorFlow. We want to see how your skills align with what we're looking for!
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 great fit for our team. Don't forget to mention any experience with cloud platforms like Azure.
Showcase Your Projects: If you've worked on any cool projects involving data science or machine learning, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they involve generative AI or advanced analytics.
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 to join our awesome team!
How to prepare for a job interview at Precise Placements
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Azure, PyTorch, and TensorFlow. Brush up on your knowledge of MLOps practices and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data science or AI projects. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how you approached problems and delivered solutions.
✨Understand the Business Context
Since this role is with a law firm, it’s beneficial to understand how data science can impact legal processes. Research how AI and analytics are transforming the legal industry and be ready to share your insights during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current projects, team dynamics, and how they measure success in their data science initiatives. This not only demonstrates your enthusiasm but also helps you gauge if the company is the right fit for you.