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Weekday Machine Learning Research Scientist Jobs

LLNL

Machine Learning Research Engineer

Livermore, CA

$146K - $222K/yr

This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning ...

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$146K - $222K/yr

This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning ...

ISEE

Research Scientist - Machine Learning

... Conducting research in the areas of: Robotics, Artificial Intelligence, Machine Learning ... in Robotics, Computer Science, Electrical Engineering, Aerospace Engineering, Mechanical ...

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$146K - $222K/yr

This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning ...

SmarterDx

Staff Machine Learning Research Scientist

$220K - $260K/yr

As a Staff Machine Learning Research Scientist at SmarterDx, you will set technical direction for cutting-edge ML research and translate it into real-world clinical impact. You'll work at the ...

Prime Team Partners

ML Research Scientist

Seattle, WA · On-site

$190/hr

Machine Learning Research Scientist Location: Hybrid - SOLU,Seattle, WA) Compensation: $190-230k base comp, + start up equity Our Seattle based client, a fastgrowing earlystage team, is seeking a ...

DISCO

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

This role involves developing advanced algorithms, optimizing research processes, and mentoring ... Science, Machine Learning, Statistics or a related discipline • Proven track record of impactful ...

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Weekday Machine Learning Research Scientist information

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$50.5K

$130.1K

$174K

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

As of Jun 5, 2026, the average yearly pay for weekday 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 a Weekday Machine Learning Research Scientist, and why are they important?

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

What cities are hiring for Weekday Machine Learning Research Scientist jobs? Cities with the most Weekday Machine Learning Research Scientist job openings:
What are the most commonly searched types of Machine Learning Research Scientist jobs? The most popular types of Machine Learning Research Scientist jobs are:
What states have the most Weekday Machine Learning Research Scientist jobs? States with the most job openings for Weekday Machine Learning Research Scientist jobs include:
Weekday Machine Learning Research Scientist jobs near you
Senior / Staff Machine Learning Research Scientist, Agents

Senior / Staff Machine Learning Research Scientist, Agents

Scale AI

Seattle, WA • On-site

Full-time

Posted 24 days ago

Job description

Job Summary:
Scale AI is a leading AI data foundry focused on accelerating the development of AI applications. The role of Senior / Staff Machine Learning Research Scientist involves researching agent environments and developing data strategies to advance intelligent AI agents, collaborating with customer researchers and engineering teams to translate research into practical solutions.
Responsibilities:
• Explore the data landscape needed to advance intelligent, adaptable AI agents.
• Guide the data strategy at Scale to drive innovation.
• Contribute to impactful research publications on agents.
• Collaborate with customer researchers.
• Work alongside the engineering team to translate advancements into real-world, scalable solutions.
Qualifications:
Required:
• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally.
Preferred:
• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH.
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
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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