At a Glance
- Tasks: Build AI models for content extraction and classification from images and text.
- Company: Join Net2Source, a rapidly growing global workforce solutions company.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with potential for career advancement.
- Why this job: Make an impact in the AI field while working with cutting-edge technologies.
- Qualifications: Experience in machine learning, Python, and document AI is essential.
The predicted salary is between 36000 - 60000 £ per year.
About Us: Net2Source Inc. is one of the fastest growing diversification‑certified global workforce solutions companies with an unprecedented YoY growth of over 100% for the last 6 years, working with Fortune 1000/Global 2000 across 34 countries and 5 continents including North America, South America, Europe, Asia, Australia, and the Middle East.
About The Role
- Location: Sheffield, UK
- Mode of Work: Hybrid (2 Days Onsite in Week)
- Type: Fixed Term Employment (FTE)
- Project Duration: 12 Months (Possible Extension)
Skills
- Mandatory: Machine Learning – AIOPS
- Good to Have: Python, ServiceNow Orchestrator, Azure Cognitive Services, GenAI – LLMOps, RPA – Microsoft Power Automate, Deep Learning – AIOPS, Reinforcement Learning – AIOPS
Required Experience
- Strong experience in Document AI Intelligent document processing using traditional models and Generative AI, particularly with open‑source models to achieve business outcomes.
- Experience delivering production-ready solutions in Python with a focus on machine learning, deep learning, natural language processing, generative AI, image processing and OCR; all additional positives.
- Experience with frameworks such as TensorFlow, PyTorch, Hugging Face, Spacy, OpenCV, Regex or equivalents.
- Experience delivering safe code to production focusing on cybersecurity and resilience of the application and APIs.
Nice to Have
- Experience using PostgreSQL for data storage and management.
- Proficiency with Azure’s core services like Azure Virtual Machines, Azure CLI, Azure Kubernetes Service (AKS), and Azure DevOps.
- Experience releasing to production in teams at a high cadence.
Responsibilities
- Build production‑ready models to drive content extraction and classification from images and text‑based sources.
- Work closely with business teams to understand requirements and iteratively design and develop solutions.
- Collaborate with product managers and technical teams: create tests, iterate new and existing products and features.
- Design and build Python MLOCR‑based components, supporting the product development lifecycle including deployment, testing and production support of the application.
Additional Details
- Seniority level: Mid‑Senior level
- Employment type: Full‑time
- Job function: Information Technology
- Industries: Staffing and Recruiting
Machine Leaning Engineer employer: Net2Source (N2S)
Net2Source Inc. is an exceptional employer, offering a dynamic work environment in Sheffield, UK, where innovation meets collaboration. With a strong focus on employee growth and development, we provide opportunities to work on cutting-edge AI projects while enjoying a hybrid work model that promotes work-life balance. Our culture fosters inclusivity and creativity, making it an ideal place for Machine Learning Engineers to thrive and contribute to impactful solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Leaning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Net2Source. A friendly message on LinkedIn can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for the interview! Brush up on common machine learning concepts and be ready to discuss your past experiences. Practice makes perfect, so do some mock interviews with friends.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, you might find exclusive job listings that aren’t posted elsewhere.
We think you need these skills to ace Machine Leaning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with machine learning, Python, and any relevant frameworks like TensorFlow or PyTorch. We want to see how your skills match 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. Keep it concise but engaging – we love a good story!
Showcase Your Projects:If you've worked on any cool projects related to document AI or generative AI, make sure to mention them! We’re keen to see real-world applications of your skills, so don’t hold back on sharing your achievements.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our awesome team at StudySmarter!
How to prepare for a job interview at Net2Source (N2S)
✨Know Your Tech Inside Out
Make sure you’re well-versed in the key technologies mentioned in the job description, like Python and machine learning frameworks. Brush up on your experience with TensorFlow, PyTorch, and any relevant open-source models. Being able to discuss specific projects where you've applied these skills will impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous roles, especially those related to document AI and intelligent processing. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to see your thought process and impact.
✨Understand the Business Context
Familiarise yourself with how machine learning can drive business outcomes, particularly in the context of the role. Be ready to explain how your work can align with the company’s goals and contribute to their success. This shows that you’re not just a techie but also understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, project timelines, and how success is measured in this role. This not only demonstrates your interest in the position but also helps you gauge if the company culture and expectations align with your career goals.
