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Overnight Machine Learning Research Scientist Jobs

DISCO

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

MongoDB

Senior Research Scientist

Palo Alto, CA · On-site

$115K - $147K/yr

They are seeking a Senior Research Scientist to contribute to the development of cutting-edge AI models, focusing on machine learning research and the practical deployment of large neural networks.

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Overnight Machine Learning Research Scientist information

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$50.5K

$130.1K

$174K

How much do overnight machine learning research scientist jobs pay per year?

As of Jun 9, 2026, the average yearly pay for overnight machine learning research scientist in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Overnight Machine Learning Research Scientist, and why are they important?

To thrive as an Overnight Machine Learning Research Scientist, you need a solid background in computer science, statistics, and mathematics, typically with a graduate degree in a related field. Proficiency in Python, TensorFlow or PyTorch, and experience with large-scale data systems are commonly required, along with relevant research publications or certifications. Strong problem-solving abilities, self-motivation, and clear written communication help you excel when working independently during overnight hours. These skills ensure effective research progress, continuous machine learning model development, and successful collaboration across time zones.

What are the unique challenges of working as an Overnight Machine Learning Research Scientist, and how is collaboration typically managed during off-hours?

As an Overnight Machine Learning Research Scientist, one of the unique challenges is maintaining effective communication and collaboration with teams that primarily work during daytime hours. To address this, organizations often utilize detailed handover notes, asynchronous communication tools, and regular overlap meetings to ensure research progress is continuous and aligned. You may also find that overnight shifts allow for uninterrupted experimentation and model training, which can be advantageous for large-scale computational tasks. However, adapting to the overnight schedule and balancing it with personal well-being is essential for long-term success in this role.

What does an Overnight Machine Learning Research Scientist do?

An Overnight Machine Learning Research Scientist is responsible for conducting research and developing new machine learning models and algorithms during overnight shifts. Their work often involves running large-scale experiments, analyzing data, and collaborating with global teams in different time zones. These scientists help ensure that research and development work continues seamlessly around the clock, accelerating innovation and supporting real-time projects. The overnight schedule may also involve monitoring models in production and troubleshooting any issues that arise during off-hours.
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Overnight Machine Learning Research Scientist jobs near you
Infographic showing various Overnight Machine Learning Research Scientist job openings in the United States as of May 2026, with employment types broken down into 9% As Needed, 27% Full Time, 55% Part Time, and 9% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.
Machine Learning Research Scientist, Reasoning

Machine Learning Research Scientist, Reasoning

Scale AI

San Francisco, CA • On-site

Full-time

Posted 19 days ago

Job description

Job Summary:
Scale AI is a leading AI data foundry focused on accelerating the development of AI applications. They are seeking a Machine Learning Research Scientist with expertise in reasoning within large language models to contribute to impactful research, collaborate with external researchers, and work closely with engineering teams to implement advancements in AI solutions.
Responsibilities:
• Study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents.
• Identify the most effective data sources and methodologies for improving LLM reasoning.
• Contribute to impactful research on language model reasoning.
• Collaborate with external researchers.
• Work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.
Qualifications:
Required:
• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow.
• Skilled at rapidly interpreting research literature and turning new ideas into working prototypes.
• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).
• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.
• Strong written and verbal communication skills, along with the ability to work effectively across teams.
Preferred:
• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.
• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.
• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.
• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.
• Proficiency in cloud-based ML development, with experience in AWS or GCP environments.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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