At a Glance
- Tasks: Design data pipelines and develop ML models to enhance our innovative platform.
- Company: Join Tadaweb, a pioneering tech company on a mission to make the world safer.
- Benefits: Enjoy a hybrid work model, team-focused culture, and exciting social events.
- Why this job: Make a real-world impact in a collaborative environment with cutting-edge technology.
- Qualifications: Experience in data engineering and machine learning, proficient in Python and relevant tools.
- Other info: We value diverse perspectives and offer a supportive workplace for all.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Tadaweb is a pioneering technology company with roots in Luxembourg and a growing global presence, with offices in the United Kingdom, France, and the United States. For over 13 years, we’ve been on a mission to make the world a safer place by empowering analysts with the tools they need to access the right information at the right time. Our cutting-edge SaaS platform revolutionizes PAI and OSINT investigations, making them faster, smarter, and more effective, all while adhering to the highest ethical standards by relying solely on publicly available information and supporting our clients’ policies. Renowned for our “nothing is impossible” ethos, we prioritize trust, transparency, and innovation in everything we do.
About the Role:
We are looking for a Machine Learning Engineer with Data Engineering expertise to help scale our platform. In this hybrid role, you’ll design data pipelines, develop ML models, and work across data and AI systems to enhance our platform’s capabilities. If you thrive in a collaborative, fast-moving environment and want to make a real-world impact, we’d love to hear from you!
Scope of Work:
- Machine Learning Engineering
- Design, develop, evaluate, and deploy machine learning models for production.
- Optimize model performance based on key metrics for scalability, reliability, and real-world impact.
- Build and maintain end-to-end ML pipelines, including data preprocessing, model training, deployment, and monitoring.
- Work closely with cross-functional teams to integrate ML models into our SaaS platform for PAI and OSINT investigations.
- Develop, maintain, and optimize scalable data pipelines for ingesting, processing, and storing large volumes of data.
- Ensure data quality, consistency, and availability to support ML workflows.
- Work with ELT processes and implement Medallion (Bronze/Silver/Gold) architecture to structure and optimize data transformation.
- Align data infrastructure with business needs and product strategy for PAI and OSINT.
- System Optimization & Support
- Monitor, test, and troubleshoot data and ML systems for performance improvements.
- Recommend and implement enhancements to data pipelines, ML workflows, and system reliability.
- Ensure seamless integration of new ML models and data-driven features into production.
Your Profile:
- Experience in both data engineering and machine learning, with a strong portfolio of relevant projects.
- Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing.
- Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka.
- Strong understanding of SQL, NoSQL, and data modeling.
- Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions.
- Knowledge of MLOps practices and tools, such as MLflow or Kubeflow.
- Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems.
- A collaborative mindset and ability to work in a fast-paced, small team environment.
You get bonus points if you have any of the following:
- Experience working with geospatial data or network graph analysis.
- Familiarity with PAI and OSINT tools and methodologies.
- Hands-on experience with containerization technologies like Docker.
- Understanding of ethical considerations in AI, data privacy, and responsible machine learning.
Our Offer:
- The opportunity to join a growing tech company, with strong product-market fit and an ambitious roadmap.
- The chance to join a human-focused company that genuinely cares about its employees and core values.
- A focus on performance of the team, not hours at the desk.
- A social calendar including family parties, games nights, annual offsites, end of the year events and more, with an inclusive approach for both younger professionals and parents.
Tadaweb is an equal opportunities employer, and we strive to have a team with diverse perspectives, experiences and backgrounds.
Our culture:
Our company culture is driven by the core values of family first, nothing is impossible and work hard, play harder. We provide a healthy and positive culture that cares about employee wellbeing by creating a great workplace and investing in our employees' learning and development. Our leaders aspire to the philosophies of extreme ownership, and servant leadership.
Machine Learning Engineer with Data Engineering expertise (London) employer: Tadaweb
Contact Detail:
Tadaweb Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer with Data Engineering expertise (London)
✨Tip Number 1
Familiarise yourself with Tadaweb's mission and values. Understanding their focus on ethical standards and innovation will help you align your responses during interviews, showcasing how your personal values resonate with theirs.
✨Tip Number 2
Highlight your experience with specific tools mentioned in the job description, such as TensorFlow or Apache Airflow. Be prepared to discuss relevant projects where you've successfully implemented these technologies, as this will demonstrate your hands-on expertise.
✨Tip Number 3
Network with current employees or alumni who work at Tadaweb. Engaging with them can provide insider insights about the company culture and expectations, which can be invaluable during your interview process.
✨Tip Number 4
Prepare to discuss real-world applications of machine learning and data engineering in the context of PAI and OSINT. Being able to articulate how your skills can contribute to Tadaweb's mission will set you apart from other candidates.
We think you need these skills to ace Machine Learning Engineer with Data Engineering expertise (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in both machine learning and data engineering. Include specific projects that demonstrate your proficiency with Python, TensorFlow, and data pipeline tools like Apache Airflow.
Craft a Compelling Cover Letter: In your cover letter, express your passion for the role and how your skills align with Tadaweb's mission. Mention your understanding of ethical considerations in AI and how you can contribute to their innovative culture.
Showcase Relevant Projects: Include a portfolio or links to relevant projects that showcase your ability to design and deploy ML models and data pipelines. Highlight any experience with cloud platforms and MLOps practices.
Prepare for Technical Questions: Anticipate technical questions related to machine learning algorithms, data processing techniques, and system optimisation. Be ready to discuss your problem-solving approach and past experiences in detail.
How to prepare for a job interview at Tadaweb
✨Showcase Your Projects
Prepare to discuss your portfolio of machine learning and data engineering projects. Highlight specific challenges you faced, the solutions you implemented, and the impact of your work. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Company’s Mission
Familiarise yourself with Tadaweb's mission to empower analysts and their focus on ethical standards. Be ready to discuss how your values align with theirs and how you can contribute to making the world a safer place through technology.
✨Brush Up on Technical Skills
Make sure you're comfortable discussing key technologies mentioned in the job description, such as Python libraries (TensorFlow, PyTorch), data pipeline tools (Apache Airflow, Spark), and cloud platforms (AWS, Azure). Be prepared to answer technical questions or even solve problems on the spot.
✨Demonstrate Collaboration Skills
Since the role involves working closely with cross-functional teams, be ready to share examples of how you've successfully collaborated in the past. Highlight your ability to communicate effectively and adapt to different team dynamics in a fast-paced environment.