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AI / ML Engineer (Hybrid)

About SEON

Are you a technically skilled, hands-on engineer that’s passionate about AI & machine learning? Join us at SEON and explore the opportunity to join a world-class research and development organization that is also passionate about creating great data experiences for our software engineers. Those great experiences ensure that we can deliver amazing solutions to the customers that we are obsessed with! 

SEON provides an API-first solution that helps our customers (many of the world's leading providers of digital experiences in financial services, insurance, entertainment, etc) defend their customers from Fraud and Financial Crimes. With over 250 Fraud Fighters across four global offices (Austin, Budapest, London, and Jakarta), our goal remains unwavering: to make the internet a safe place for businesses and customers to transact. Our achievements, including a record-breaking Series B funding round and recognition in TechCrunch, has led to recognition as the World’s quickest-growing fraud prevention company. We take pride in our rapid growth and our mission to democratize fraud-fighting while empowering the best online businesses. Join us in our journey to make the internet a safer space for everyone.

What you’ll do:

  • Develop and enhance ML and GenAI applications by designing and implementing cutting-edge models, leveraging deep learning, transformers, and LLMs for real-world use cases.
  • Maintain and optimize data science and MLOps infrastructure, ensuring scalability, reliability, and efficiency across training, deployment, and monitoring pipelines.
  • Transform research prototypes into scalable, production-ready AI systems, focusing on robustness, performance, and seamless integration into existing platforms.
  • Train, fine-tune, and continuously improve ML and GenAI models, optimizing for accuracy, fairness, efficiency, and real-time adaptability.
  • Develop and refine model monitoring, evaluation, and drift detection systems to ensure sustained model performance and prevent degradation over time.
  • Write production-quality, maintainable, and well-tested code, following best practices in software engineering and MLOps.
  • Develop and deploy AI/ML solutions in Python, following best practices in software engineering, containerization (Docker, Kubernetes), and cloud deployment.
  • Develop and optimize real-time ML pipelines, integrating stream processing frameworks (e.g., EventBridge, Kafka, Flink, Spark Streaming) to enable low-latency predictions and continuous model updates.
  • Implement explainability and interpretability techniques to increase trust and transparency in ML/GenAI models.
  • Stay up to date with and work with modern LLM frameworks (e.g., Hugging Face, LangChain, LlamaIndex) to build, fine-tune, and deploy generative AI applications efficiently.
  • Collaborate with cross-functional teams, including engineering, product, and other development teams, to integrate AI capabilities into business solutions.
  • Stay up to date with emerging AI trends and evaluate their applicability to our business needs.

What you'll bring:

  • Show deep expertise in data science.
  • Experience with scalable application development in Python.
  • Strong software engineering skills, including RESTful API development, containerization (Docker, Kubernetes), and cloud deployment.
  • Hands-on experience with machine learning and generative AI, including model training, fine-tuning, and optimization.
  • Proficiency in MLOps (CI/CD for ML, monitoring, model versioning, and deployment pipelines).
  • Solid understanding of ML algorithms.
  • Familiarity with modern LLM frameworks (e.g., Hugging Face, LangChain, LlamaIndex) and vector databases(e.g., Pinecone, Weaviate, FAISS).
  • Knowledge of stream processing frameworks (e.g., Kafka, Flink, Spark Streaming) for real-time ML inference.
  • Fundamental knowledge of data quality, testing methodologies, and model evaluation techniques.
  • Commitment to lifelong learning, staying up to date with the latest AI/ML advancements and best practices.
  • Out-of-the-box thinking, combined with the ability to adapt to a fast-paced environment.
  • Excellent problem-solving skills.
  • Fluent English.

What we offer

  • Competitive salary and incentive compensation structure
  • Hybrid work model
  • Extensive Benefits package (Health, Dental, Vision, Disability, 401k w/ match, etc.)
  • Best-in-class tech gear
  • Immediate impact on a smart, growing, global team
  • Access to continuous development tools & a strong coaching culture
  • Employee stock ownership plan (ESOP)
  • Generous vacation & leave policies
  • Complimentary weekly language courses
  • Weekly in-office lunch delivery budget

What’s next:

Does that sound good to you? Great, we can’t wait to hear from you! Would you like to learn more about what it’s like to work at SEON first?
👉 https://seon.io/careers/

Average salary estimate

$100000 / YEARLY (est.)
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$80000K
$120000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About AI / ML Engineer (Hybrid), SEON Technologies

At SEON, we’re on the lookout for an innovative AI / ML Engineer to join our dynamic team and be a key player in our mission to make the internet a safer place for businesses and consumers alike. In this hybrid role, you’ll dive deep into developing and enhancing machine learning and generative AI applications that could transform industries such as finance, insurance, and entertainment. Your days will be filled with designing cutting-edge models, optimizing our data science infrastructure, and creating robust production-ready AI systems. You'll be working with state-of-the-art technologies like deep learning, transformers, and various frameworks, ensuring that our solutions are scalable and efficient. Your contributions will help streamline the pipeline from training to deployment while maintaining high standards in model performance, explainability, and adaptability. Additionally, you’ll collaborate with talented cross-functional teams to integrate AI capabilities into our business solutions. With our rapid growth and recent award as the world’s fastest-growing fraud prevention company, there hasn’t been a better time to join SEON! If you have a passion for AI and a drive to push the boundaries of technology, this could be the adventure you’ve been waiting for!

Frequently Asked Questions (FAQs) for AI / ML Engineer (Hybrid) Role at SEON Technologies
What are the key responsibilities of an AI / ML Engineer at SEON?

As an AI / ML Engineer at SEON, you will develop and enhance machine learning applications, design cutting-edge models, and maintain and optimize data science infrastructure. Your role will involve transforming prototypes into production-ready systems, training and fine-tuning models for real-world applications, and implementing robust monitoring and evaluation systems to ensure ongoing performance.

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What qualifications are required for the AI / ML Engineer position at SEON?

To thrive as an AI / ML Engineer at SEON, you should possess deep expertise in data science, strong software engineering skills particularly in Python, and hands-on experience with machine learning and generative AI. Familiarity with MLOps practices, modern LLM frameworks, and stream processing technologies will also be essential for success.

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What technologies does an AI / ML Engineer at SEON work with?

In the role of an AI / ML Engineer at SEON, you will work with cutting-edge technologies including deep learning frameworks, transformers, Docker, Kubernetes, and various stream processing frameworks such as Kafka and Flink. You'll also utilize modern LLM frameworks like Hugging Face and LangChain to build and deploy innovative AI solutions.

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How does SEON support the continuous development of its AI / ML Engineers?

SEON is committed to the professional growth of its AI / ML Engineers by providing access to continuous development tools, a robust coaching culture, and opportunities to learn the latest in AI and ML advancements. With competitive benefits and a culture that fosters lifelong learning, you'll have ample opportunity to expand your skills and knowledge.

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What is the work culture like for AI / ML Engineers at SEON?

The work culture for AI / ML Engineers at SEON is collaborative and innovative, marked by an enthusiastic team that is passionate about technology and making a difference in fraud prevention. The hybrid work model allows for flexibility, while the inclusive environment encourages creativity and out-of-the-box thinking.

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Common Interview Questions for AI / ML Engineer (Hybrid)
Can you explain your experience with machine learning algorithms?

When answering this question, highlight specific algorithms you've worked with, detailing your role in training and optimizing them for particular projects. Provide examples of the challenges faced and the results achieved, demonstrating how your expertise contributes to the field of AI.

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Describe how you would approach designing a scalable machine learning model.

Focus on outlining your process step-by-step, from gathering and processing data to selecting the right algorithms and frameworks. Emphasize on considerations for MLOps, such as model monitoring and versioning, to ensure scalability and performance in production.

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What experience do you have with deep learning frameworks?

Discuss the frameworks you are familiar with, such as TensorFlow or PyTorch, and provide examples of projects where these frameworks were utilized. Highlight any innovative solutions or techniques you implemented to enhance model performance.

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How do you ensure the models you develop are interpretable and explainable?

Talk about methods you use for model evaluation, such as SHAP values or LIME, and how you apply these techniques to improve trust in your models. Provide an example of how you addressed the challenge of model interpretability in a previous role.

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Can you provide an example of a successful MLOps pipeline you’ve built?

Clearly outline the steps you took in building the MLOps pipeline, focusing on aspects like automation, deployment, continuous integration/continuous delivery (CI/CD), and how you handled monitoring and model retraining.

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How do you stay updated on the latest trends in AI and ML?

Share your strategies for staying informed, such as following influential researchers, participating in workshops, or staying active in AI/ML forums and communities. Mention any recent trends you’re excited about and how you see them impacting your work at SEON.

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What is your experience with deploying machine learning models to production?

Provide examples of projects where you took machine learning models from development into production. Discuss the challenges you faced and how you ensured smooth deployment and ongoing maintenance.

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Describe a time when you had to troubleshoot a model that wasn't performing as expected.

Illustrate the steps you took to identify the issues, what metrics you analyzed, and how you iterated on the model or data to improve its performance. This will showcase your problem-solving skills and ability to adapt.

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What programming languages and tools do you prefer for AI/ML development?

Mention your preferred languages, such as Python, and any specific libraries or frameworks you favor. Explain why you prefer these and how they enhance your development process and the quality of the solutions you provide.

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How do you incorporate feedback from stakeholders in your AI projects?

Discuss your approach to gathering and integrating feedback from various stakeholders, including product managers or end users, and how this feedback influences your work and the continuous improvement of your models and solutions.

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Founded in 2015, SEON provides fraud detection software for industries such as Banking & Insurance, iGaming, Online Lending, Ecommerce, and more. The company is headquartered in London, United Kingdom.

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Full-time, hybrid
DATE POSTED
March 13, 2025

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