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Weekday Machine Learning Research Scientist Jobs

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 ...

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 ...

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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 Jul 14, 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 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 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 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
Staff Machine Learning Research Scientist

Staff Machine Learning Research Scientist

SmarterDx

Remote

$220K - $260K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 7 days ago

Job description

SmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
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 intersection of research, engineering, and healthcare, partnering with engineers and clinicians to build systems that deeply understand patient records and improve hospital outcomes. This is a senior, high-impact role where you'll not only execute on ambitious ideas but also shape the team's research agenda and standards.
You will be expected to operate with a high degree of autonomy-identifying promising research directions, critically evaluating academic work, and ensuring that what gets built is both scientifically sound and practically useful. Your work will directly influence how we evaluate models, detect hallucinations, and build high-quality datasets, ultimately improving the reliability of AI in healthcare.
**This role is fully remote within the US**
What You'll Do
  • Lead end-to-end ML research, from idea generation to production deployment and monitoring
  • Design, implement, and evaluate novel methods for LLM alignment on proprietary clinical data
  • Develop and rigorously evaluate approaches for hallucination detection, attribution, and model reliability
  • Build and curate high-quality datasets, with a strong emphasis on evaluation design and benchmark integrity
  • Critically assess academic literature to identify strong vs weak methods, and translate the best ideas into practice
  • Establish best practices for experimental design, including statistically sound evaluation and reproducibility
  • Collaborate cross-functionally with engineering to productionize models (MLOps, infra, deployment)
  • Develop methods for long-context and multimodal modeling (structured + unstructured clinical data)
  • Mentor other researchers and help raise the bar for research quality across the team
  • Contribute to external presence through papers, talks, and recruiting

What You Bring
  • Strong track record of ML research, ideally with publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, AAAI, etc.)
  • Proven ability to distinguish high-quality vs low-quality research, especially in fast-moving areas like LLMs
  • Deep understanding of LLM failure modes, particularly hallucinations, and how to evaluate and mitigate them
  • Experience designing rigorous evaluation frameworks and building high-quality test datasets
  • Strong intuition for dataset quality, bias, and benchmark design (data-centric AI mindset)
  • Hands-on experience training large-scale deep learning models (multi-GPU / distributed systems)
  • Deep understanding of modern neural architectures (transformers, SSMs, encoder/decoder models, etc.)
  • Strong programming skills in Python and ML frameworks such as PyTorch or JAX
  • Experience deploying ML models into production systems and monitoring their performance
  • Clear and proactive communicator, able to explain complex ideas and critique work effectively

Nice To Haves
  • Experience with inference optimization techniques (e.g., vLLM, KV caching, speculative decoding)
  • Familiarity with MLSys concepts (parallelism strategies, distributed training infrastructure)
  • Experience working with clinical or healthcare data
  • Background in retrieval systems, graph-based learning, or multimodal modeling

Our Tech Stack
  • PyTorch, Hugging Face Transformers, Python
  • AWS (MWAA), Kubernetes, SLURM
  • DeepSpeed, TorchTune
  • Snowflake, Airflow, GitHub
Compensation
$220k-260k base salary
#LI-Remote
Benefits
  • Medical, Dental & Vision - Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
  • Paid Parental Leave - Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
  • Remote-First Team - Work from anywhere in the U.S.
  • Unlimited PTO & 10 Holidays - So you can relax and recharge.
  • 401(k) with Traditional & Roth Options - Tax-advantaged retirement savings through Fidelity with a 4% match.
  • Minimal Bureaucracy - A fast-moving, high-impact environment where you can focus on what matters.
  • Incredible Teammates! - Work alongside smart, supportive, and mission-driven colleagues.

Apply