Machine Learning Engineer, AI for Chemistry project

Key Skills

Aartificial intelligence, Deep Learning, HuggingFace, Machine learning techniques, PostgreSQL, Python Programming, PyTorch

Job Description

As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying state-of-the-art multi-modal models. This role requires a deep passion for problem-solving and experimentation, moving across the full range of applied machine learning tasks from initial prototyping to building full-scale, robust solutions. While you will primarily focus on core product development, you will also serve as a critical bridge between cutting-edge AI research and real-world enterprise applications. You will be a key player in our mission to accelerate scientific discovery through machine learning.

How you will have 10X impact:

• Design and build end-to-end machine learning pipelines for training, evaluation, and deployment.
• Develop and fine-tune sophisticated multi-modal models using frameworks like PyTorch and libraries from the Hugging Face ecosystem.
• Leverage Google Cloud Platform (GCP) services to deploy and scale our ML models and infrastructure.
• Collaborate with cross-functional teams of scientists and engineers to translate research ideas into production-ready solutions.
• Stay current with the latest advancements in machine learning, particularly in multi-modal learning and generative models.

What you should have:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• At least 5 years of experience designing, building and deploying ML solutions
• Proven experience building and training deep learning models using PyTorch and the Hugging Face library
• Demonstrated experience with Large Language Models (LLMs), multi-modal models (e.g., Vision Language Models (VLMs)) and computer vision models (eg. OCR)
• Strong proficiency with Google Cloud Platform (GCP) and its core services for machine learning and data processing.
• Excellent programming skills in Python and a solid understanding of software engineering best practices.
• Hands-on experience with MLOps principles and tools (e.g., Kubeflow, MLflow, Vertex AI Pipelines) and DevOps practices (e.g., CI/CD, Docker, Kubernetes, Terraform).
• Experience with large-scale data processing and database management (e.g., PostgreSQL, SQLAlchemy).
• Experience in start-up or small team environments

It’d be great if you also had these:

• A foundational knowledge of organic chemistry concepts or experience working with chemical data (e.g., SMILES strings, molecular graphs).
• Published research papers in relevant fields

The US base salary range for this full-time position is $165,000 - $258,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.