AI Research Scientist / Machine Learning Engineer (PhD) [33320]

We are seeking a

PhD-level AI Research Scientist or Machine Learning Engineer

to develop cutting-edge AI and machine learning solutions that power next-generation products. You will work at the intersection of research and engineering, transforming advanced ML techniques into scalable, production-ready systems.

This role is open to:

• PhD graduates with 4\+ years of industry experience

in AI, machine learning, or applied research.

• Machine Learning Engineers with a PhD and 1–2 years of professional ML engineering experience

, provided they have demonstrated success deploying production ML systems.

Responsibilities

• Research, design, and develop advanced machine learning and AI models.
• Build and deploy production-ready ML systems and inference pipelines.
• Collaborate with software engineers to integrate AI capabilities into customer-facing products.
• Optimize model accuracy, efficiency, and scalability.
• Develop data pipelines, model evaluation frameworks, and experimentation workflows.
• Stay current with the latest advancements in machine learning, deep learning, LLMs, and generative AI.
• Mentor engineers and contribute to technical strategy and architecture.
• Publish or present research where appropriate and translate research into business impact.

Qualifications

• PhD in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Statistics, Applied Mathematics, or a related quantitative field.
• 4\+ years of industry experience

in AI/ML research or engineering

OR

• 1–2 years of experience as a Machine Learning Engineer

with proven experience deploying ML models into production.

• Strong programming skills in

Python

and experience with

C\+\+

,

Java

, or

Go

.

• Hands-on experience with

PyTorch

,

TensorFlow

, or

JAX

.

• Experience building scalable ML pipelines and distributed training or inference systems.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies.
• Strong understanding of algorithms, deep learning, and software engineering best practices.

Preferred Qualifications

• Experience with Large Language Models (LLMs), generative AI, multimodal models, or reinforcement learning.
• Experience with distributed systems, MLOps, Kubernetes, Docker, and CI/CD.
• Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL) are a plus.
• Startup or high-growth technology company experience.
• Strong communication skills with the ability to collaborate across research and engineering teams.