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Ml Research Engineer Jobs (NOW HIRING)

Our rapidly growing startup is seeking an AI Research Engineer to join our Foundational Models AI ... You'll be expected to design, implement, and iterate on ML experiments rapidly, contributing to ...

Research, ML

San Francisco, CA · On-site

$180K - $350K/yr

We now power search for Cursor, Cognition, HubSpot, and over 400,000 developers and have raised ... Research at Exa The ML organization sits at the heart of our mission. We train foundational models ...

Research Engineer

New York, NY · On-site

$200K - $400K/yr

Apply and develop techniques from best-in-class AI Agents, ML, and SRE research to our problem domain. Experiment with new approaches to reasoning, retrieval, codebase mapping, and agent ...

Apply and develop techniques from best-in-class AI Agents, ML, and SRE research to our problem domain. Experiment with new approaches to reasoning, retrieval, codebase mapping, and agent ...

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

Required : • An ML Research background with interests in HW co-design • Experience with Python, Pytorch, and / or JAX • Familiarity with transformer model architectures and/or inference serving ...

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

Required : • An ML Research background with interests in HW co-design • Experience with Python, Pytorch, and / or JAX • Familiarity with transformer model architectures and/or inference serving ...

Michal Mankowski, PhD the Research Engineer will join a multidisciplinary team committed to ... ML concepts and how they interact with the software scaffolding around them in real-world ...

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How much do ml research engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for ml research engineer in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What is an ML research engineer?

ML Research Engineers are professionals who combine expertise in machine learning, software engineering, and research to design, implement, and optimize algorithms and models. They work closely with data scientists and researchers to translate theoretical ideas into practical, scalable solutions. Their role often includes developing prototypes, running experiments, and contributing to academic or industry research. ML Research Engineers also stay updated with the latest advancements in the field and help integrate cutting-edge technologies into products or services.

How does an ML research engineer typically collaborate with data scientists and software engineers on projects?

Machine Learning Research Engineers often work closely with data scientists to prototype and validate models, ensuring that research findings are technically feasible and aligned with business goals. They also collaborate with software engineers to integrate machine learning models into production systems, focusing on scalability, reliability, and performance. This cross-functional teamwork requires strong communication skills and the ability to translate complex research concepts into practical engineering solutions. Regular meetings, code reviews, and joint problem-solving sessions are common in this collaborative environment.

What are the key skills and qualifications needed to thrive as an ML research engineer, and why are they important?

To thrive as an ML Research Engineer, you need a strong background in machine learning theory, programming (often in Python), and a relevant degree in computer science, mathematics, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and knowledge of data engineering tools are typically required. Creativity, strong problem-solving abilities, and effective communication help you innovate and collaborate within research teams. These skills and qualities are essential for developing cutting-edge models and solutions that advance machine learning applications.
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Infographic showing various Ml Research Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 10% Part Time, and 1% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $106,012 per year, or $51 per hour.

Senior AI/ML Research Engineer - Model development

Sunnyvale, CA • On-site

Intuitive Surgical
Manufacturing • 5 - 10K employees

$122K - $168K/yr

Full-time

Re-posted 20 hours ago


Intuitive Surgical rating

8.7

Company rating: 8.7 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.

If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.

Job Description

Primary Function of Position

We are building advanced augmented dexterity for next-generation robotic platforms. As a Senior AI/ML Research Engineer, you will develop and fine-tune the foundation models—VFMs, VLMs, and VLA models—that let our Embodied-AI system understand the surgical scene and act within it. Within a hierarchical, multimodal stack, you will own the model layer: adapting large pretrained vision and multimodal models on surgical data to extract anatomy, instruments, actions, and context from intraoperative video, and connecting perception to reasoning and action. Partnering with the broader AI/ML team, you will drive the path from offline research to robust, real-time performance in the OR.

Working within Intuitive's Future Forward research organization, you will identify, build, and fine-tune the AI/ML models and algorithms that let us deliver safe and performant embodied-AI systems. This role calls for someone equally comfortable getting hands-on with models and data and designing systems that scale.

Roles and Responsibilities

  • Develop, fine-tune, and evaluate the AI/ML models—including foundation and multimodal models—that enable the system to perceive the surgical scene and translate intent and observations into safe, performant behavior.
  • Establish strong baselines by reproducing relevant state-of-the-art approaches, then iteratively advance them with in-house models and components while keeping interfaces stable.
  • Build and maintain training and data pipelines that combine real demonstration data with simulation, and establish human-in-the-loop pipelines for continuous model improvement.
  • Define and run evaluation for model performance, repeatability, and safe failure/abort behavior, and establish the path from offline evaluation on recorded data to robust, real-time integration.
  • Partner with data and annotation teams to shape label taxonomies, quality control, and the data pipeline that feeds the models.
  • Collaborate across AI/ML research, robotics, software, and data engineering to align on interfaces and deliver models that enable rapid prototyping and learning while building toward a product solution.
Qualifications

Minimum Qualifications

  • MS or PhD in CS, EE, Robotics, or a related field, with 5+ years of applied AI/ML research experience in areas such as robot learning, embodied AI, control, or sequential decision-making.
  • Hands-on experience training policies or models from data, including imitation/behavior cloning and reinforcement learning, and fine-tuning pretrained models.
  • Experience with vision-action (VA), vision-language-action (VLA), or goal/intent-conditioned models, including models that produce action or control outputs.
  • Familiarity with world models and self-supervised predictive architectures (e.g., JEPA-style models, MAE, DINO) for learning dynamics and latent representations to support planning and control.
  • Comfort building training and evaluation loops over both simulated and real-world data.
  • Strong software and ML-engineering skills in Python and C++, with proficiency in one or more of PyTorch/TensorFlow/JAX.
  • A research-and-prototyping mindset: comfortable working in ambiguity, framing open-ended problems, running rapid experiments, and reading and reproducing recent papers to pull promising techniques into practice.
  • Sound judgment about the path from prototype to product: writing code others can build on, knowing when to optimize versus when to move fast, and thinking ahead about data quality, evaluation, and robustness even at the research stage.
  • Solid foundations in linear algebra, probability, and optimization, enough to reason about and debug model behavior from first principles.
  • Comfort collaborating across a multidisciplinary team (ML, robotics, software, and clinical/domain experts) and communicating tradeoffs and findings clearly.

Preferred Qualifications

  • Modern policy architectures: diffusion policies, transformer policies, action chunking (e.g., ACT), and generalist robot policies (RT-X / OpenVLA-style).
  • DAgger / human-in-the-loop and data-flywheel pipeline experience.
  • Sim-to-real transfer and domain randomization (e.g., NVIDIA Isaac Sim).
  • Teleoperation, kinematics, and real-time on-robot deployment.
  • Publications at CoRL, RSS, ICRA, IROS, or NeurIPS.
Additional Information

Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19.  Details can vary by role.

Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.

Mandatory Notices

U.S. Export Controls Disclaimer:  In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status.

Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process).  

For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. 

We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.

Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.

This position may be filled at a different job level than listed here depending on
business need and/or on the selected candidate’s experience, knowledge and skills.
Compensation will be based primarily on the job level at which the role is filled and the
candidate’s qualifications, consistent with applicable law.

We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.

Base Salary Range Region 1:$196,800 - $283,200
Base Salary Range Region 2: $167,300 - $240,700
Shift: Day
Workplace Type: Onsite - This job is fully onsite.


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