AI SCORE 8.5

Senior Research Scientist Engineer - Foundational ML

$300K–$800K/year
HybridAI/Big DataVisaRelocation

About the Role

We are seeking a Senior Research Scientist Engineer to join our team remotely. This role offers an exceptional opportunity to work at the intersection of technology and life sciences, utilizing advanced machine learning techniques to solve complex biophysical problems.

What You'll Do

  • Architect & Scale: Design and deploy sophisticated deep learning frameworks and LLM architectures to accelerate the discovery of transformative therapeutic compounds.
  • Optimize Workflows: Champion the integration of ML workflows—including pre-training, post-training, and inference—within a custom, high-speed supercomputing infrastructure.
  • Engineer for Impact: Write high-performance Python code to deploy neural networks that surpass the limitations of traditional quantum chemistry models.
  • Drive Generative Innovation: Lead the evolution of generative models and multimodal learning to design optimized biological macromolecules and proteins.
  • Synthesize & Innovate: Collaborate with a diverse team of chemists and biologists to translate cutting-edge LLM breakthroughs into practical, scalable scientific tools.

Requirements

  • LLM & Generative Mastery: Proven expertise in developing and training Large Language Models (LLMs), including experience in scaling large model training and optimizing complex inference workflows.
  • Programming Expertise: Expert-level proficiency in Python (additional coding experience is a significant plus) and standard frameworks like PyTorch, JAX, or TensorFlow.
  • Elite Background: A distinguished record of innovation, likely originating from high-impact tech environments (e.g., OpenAI, Google DeepMind, Meta, Anthropic, NVIDIA) or premier academic labs focused on protein language models.
  • Scientific Versatility: While experience in drug discovery or biomolecular simulation is helpful, no prior scientific background is required for candidates with exceptional ML credentials.
  • Intellectual Rigor: A desire to work in a high-energy research culture that rewards cross-functional ingenuity and rigorous scientific inquiry.

What We Offer

  • Competitive salary ranging from $300,000 to $800,000, based on experience.
  • Comprehensive relocation support to assist with your move.
  • Full visa sponsorship for qualified candidates.
  • Sign-on bonuses and robust variable bonuses.
  • A collaborative and innovative work environment.
Why This Job8.5 of 10

This Senior Research Scientist Engineer role offers a unique opportunity to work at the forefront of AI and life sciences, with a competitive salary and relocation support.

Salary Range
Required
0/1
Optional
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Bonus
0/1

Who Will Succeed Here

Proficiency in Python and experience with deep learning frameworks such as TensorFlow and PyTorch, with a strong focus on deploying scalable LLM architectures for biophysical applications.

A self-motivated and adaptable mindset suited for a hybrid work environment, capable of balancing independent research with collaborative projects across diverse teams.

Strong analytical skills with a proven track record of applying machine learning techniques to real-world problems, particularly in the life sciences sector, demonstrating the ability to translate complex data into actionable insights.

Learning Resources

Deep Learning with Python and PyTorchcourse

Career Path

Senior Research Scientist Engineer - Foundational ML(Now)Lead Machine Learning Engineer(1-2 years)Director of AI Research(3-5 years)

Market Overview

Market Size 2024
$15.7B
Annual Growth
22.3%
AI Adoption
48%
Investment
+150%
Labour Demand
+30%
Avg Salary
$145K

Skills & Requirements

Required
PythonMachine LearningDeep Learning
Growing in Demand
Natural Language Processing (NLP)Cloud Computing (AWS, Azure)Data Engineering
Declining
R (for statistical computing)Matlab

Domain Trends

Rise of Large Language Models (LLMs)
LLMs are transforming the landscape of AI applications, with a 70% increase in companies adopting them for various use cases.
Shift Towards Federated Learning
Federated learning is gaining traction, with a projected growth of 40% in its adoption as organizations prioritize data privacy.
Increased Focus on Explainable AI
The demand for explainable AI solutions has surged by 55% as companies seek transparency in AI decision-making processes.

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