Machine Learning (ML) Engineer - Applied

ModelCat AI·Remote(Europe)
Data & Analytics
Excel

WFA Digital Insight

As demand for Edge AI solutions continues to surge, with the market expected to grow exponentially in the next few years, the need for skilled Machine Learning Engineers is at an all-time high. ModelCat AI, a venture-backed startup, is at the forefront of this revolution with its innovative AutoML platform. With the ability to compress months of model development into mere hours, the company is transforming the way businesses approach AI. Candidates looking to apply should be well-versed in machine learning frameworks, have a strong grasp of Python, and experience in cloud platforms. It's a unique opportunity to be part of a pioneering effort in AI, with the potential for significant professional growth in the rapidly evolving Edge AI landscape.

Job Description

About the Role

The Machine Learning Engineer position at ModelCat AI represents a unique opportunity to be at the forefront of Edge AI innovation. As a member of the team, you will play a pivotal role in the development and expansion of the company's AutoML platform. This platform is designed to revolutionize the way companies develop AI models for embedded, edge, and IoT devices, reducing what was previously a 12-24 month process into a mere 24-48 hours.

Day-to-day, you will be working closely with a team of talented engineers and data scientists to advance the capabilities of the AutoML system. This will involve not only the development of new features but also the integration of new machine learning use-cases across various data domains. Your work will be instrumental in driving the company's mission forward, with a direct impact on how businesses and industries approach AI.

What You Will Do

  • Contribute to the development and enhancement of the AutoML system for Edge AI, focusing on pipelines that combine deep-learning and conventional algorithms for embedded devices.
  • Develop and improve platform features across compute clusters and the web application, ensuring seamless integration and scalability.
  • Define abstractions and contribute to the architecture of cloud, cluster, and embedded components, ensuring a robust and reliable system.
  • Integrate new ML use-cases across a broad range of data domains, including time-series, audio, object re-identification, and segmentation, among others.
  • Work on the optimization and deployment of AI solutions for edge devices, utilizing TinyML frameworks to create models that fit a range of chip sizes and memory constraints.
  • Deploy ML and non-ML algorithms on embedded targets, ensuring efficient and effective performance.
  • Partner with data scientists on data strategies, preprocessing pipelines, and model training workflows to ensure coherence and maximized outcomes.
  • Stay current with Edge AI and AutoML advancements, incorporating new techniques and methodologies into the platform.
  • Document your work and contribute to technical reports, ensuring clarity and transparency in the development process.

What We Are Looking For

  • A Master's degree in Computer Science, Electrical Engineering, or a related field, with a PhD being a significant plus.
  • 4+ years of relevant industry experience in machine learning, with a strong emphasis on AutoML and Edge AI experience.
  • Strong Python skills, with the ability to write production-quality code; proficiency in C/C++ is a plus.
  • Solid command of ML frameworks such as TensorFlow, PyTorch, and ONNX.
  • Proficiency with the standard data science toolset: scikit-learn, OpenCV, pandas.
  • Comfortable working in Linux-based development environments.
  • Experience in onboarding new ML use-cases and expanding into new data domains.
  • Excellent problem-solving skills and strong written and verbal English communication skills.

Nice to Have

  • Experience with cloud platforms, such as AWS, and web technologies, including Node.js and REST APIs.
  • Familiarity with compute cluster tools like Ray and Optuna.
  • Knowledge of model compression techniques: pruning, quantization, transfer learning, and knowledge distillation.
  • Experience defining software architecture for ML systems.
  • Familiarity with CI/CD practices and understanding of embedded systems concepts.

Benefits and Perks

  • The opportunity to work on cutting-edge technology that is revolutionizing the AI landscape.
  • Collaborative and dynamic work environment with a team of talented professionals.
  • Professional development opportunities, including training and education support.
  • Competitive compensation package and benefits.
  • Flexible work arrangements, including remote work options.
  • Access to the latest tools and technologies in the field of machine learning and Edge AI.
  • Recognition and reward for outstanding performance and contributions to the company's mission.

How to Stand Out

  • Ensure you have a strong portfolio showcasing your machine learning projects, especially those related to Edge AI and AutoML.
  • Highlight your experience with machine learning frameworks and Python in your resume and cover letter.
  • Prepare to talk about your problem-solving approach and how you handle complex data sets and model training workflows.
  • Be ready to discuss your understanding of the current state of Edge AI and AutoML, and how you see the field evolving.
  • Consider reaching out to current or former employees to gain insights into the company culture and what makes a candidate successful in this role.
  • Tailor your application to the specific requirements of the job, emphasizing your unique strengths and qualifications.
  • Practice whiteboarding exercises to improve your ability to explain complex technical concepts clearly and concisely.

This is a remote position listed on WFA Digital, the platform for professionals who work from anywhere. Browse more remote jobs across all categories.