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Senior Research Engineer

Albert Invent

Albert Invent

Posted on Wednesday, July 3, 2024

Albert is on a mission to foster a software platform which uses big data and machine learning to drastically accelerate the invention of new formulations and novel materials. We are looking for a Senior Research Engineer to join our data science team.

You will play a critical role in our mission to streamline chemical formulation workflows and provide data-driven insights to researchers worldwide. We are seeking a highly motivated and talented individual with a passion for innovation and a strong background in data science and engineering.

In this role, you will have the opportunity to unleash your creativity, intelligence, and curiosity to create AI/ML applications and tools that will empower chemists and researchers at some of the world’s leading chemical manufacturers to push the boundaries of innovation. If big, cross-disciplinary technical challenges excite you, join our team as we push to disrupt digital manufacturing and material science innovation.

What you’ll do:

  • As a key contributor to the Albert data ecosystem, you will shape and expand its data science capabilities to drive internal and external projects that deliver data driven tools for rapid innovation in the materials science industry.
  • Help drive the development of the Albert Data Science Toolkit, an open-source python SDK, that provides data scientists with the necessary tools to work effectively with Albert.
  • Contribute towards the development of AI/ML algorithms that support the research of chemical formulators across the world.
  • Design, implement and evaluate advanced AI/ML algorithms, including deep learning models and Gaussian processes, to enhance the accuracy and efficiency of the platform’s ability to predict material properties of chemical formulations.
  • Interact with, learn from, and help build tools for chemists and researchers at some of the world’s largest chemical manufacturers.
  • Mentor and train junior team members, helping them grow and develop their skills.


For us, qualifications are whatever enables you to meet (and exceed) your performance objectives. You should highlight the relevance of your background in a brief cover letter along with your comments on the following characteristics of successful candidates for this position:

  • You are a natural leader and a great communicator. You enjoy presenting your work and collaborating with others to find innovative and efficient solutions to challenging problems.
  • You are excited by the startup culture and are invigorated by the idea of solving complex problems and enhancing the way people think about AI/ML as a tool for innovation.
  • You love working with big data and enjoy the challenges of designing algorithms that work at scale and deploying them as commercial solutions.
  • You are familiar with state-of-the-art statistical and deep learning techniques and have hands-on experience deploying models.

Preferred experience:

  • A masters or PhD in a technical discipline such as computer science, data science, mathematics, physics, chemistry, or another related field with a minimum of 3 years of professional level research experience developing statistical/deep learning-based solutions.
  • A Bachelors in a technical discipline with 7-10 years of industry experience working with machine learning models and infrastructure.
  • Experience using a mainstream tensor network library such as PyTorch, Tensorflow/Keras, TensorRT, etc…) and using it to implement/train/deploy deep learning models.
  • Experience working with standard and/or deep gaussian process regression.
  • Experience developing production level data science libraries.
  • Adept in the Python programming language and use of typing extensions.

Bonus Points:

  • Ability to demonstrate a sophisticated understanding of the mathematics involved in statistical/deep learning techniques.
  • Experience in representation learning.
  • Exposure to concepts from chemistry such as chemical structure, material properties, and hazards. Experience working with and developing unsupervised models.
  • Experience working with strongly typed programming languages.
  • A good sense of humor.