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Ml Research Engineer Jobs (NOW HIRING)

Specter

ML Research Engineer

San Francisco, CA · On-site

The Role Specter is hiring a perception AI engineer responsible for turning sensor data pipelines into actionable insights for our customers. Responsibilities: * Implementing and deploying a variety ...

CACI

Senior AI/ML Research Engineer

Florham Park, NJ

$109K - $150K/yr

Senior AI/ML Research Engineer Job Category: Engineering Time Type: Full time Minimum Clearance Required to Start: Top Secret Employee Type: Regular Percentage of Travel Required: Up to 10% Type of ...

Apple Inc.

$184K - $324K/yr

AIML - Senior ML Research Engineer, AFM Safety Cupertino, California, United States Machine Learning and AI Join us as we build safe and reliable foundation models for Apple's products. Our team ...

Phonic

Research Engineer

San Francisco, CA · On-site

About The Role As a Research Engineer at Phonic, you'll sit at the intersection of cutting-edge ML research and production engineering, working directly on the core systems that make Phonic's voice ...

Gladstone

Research Engineer (ML)

San Francisco, CA

$88K - $120K/yr

The Finkbeiner Lab at Gladstone Institutes is seeking a ML Research Engineer to join a team of computer scientists applying AI/ML in diverse biomedical research projects. This involves working ...

Posted today

Phonic, Inc.

Research Engineer

San Francisco, CA · On-site

About The Role As a Research Engineer at Phonic, you'll sit at the intersection of cutting-edge ML research and production engineering, working directly on the core systems that make Phonic's voice ...

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How much do ml research engineer jobs pay per year?

As of Sep 11, 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.

ML Research Engineer

San Francisco, CA • On-site

Specter
See more jobs at Specterexternal

Full-time

Re-posted 25 days ago

Job description

Company Background
Specter's mission is to help automate the physical world.
Today, we build video sensors with state-of-the-art AI agents that answer any question, anywhere in their environments. Our systems can automatically detect and reason about any physical activity captured on camera, from security incidents (e.g. perimeter intrusion, theft, LPR), to safety monitoring (e.g. PPE detection, injured people), to operational efficiency (e.g. material tracking, congestion monitoring). We offer both long range wireless (1km range) and wired sensor variants to suit any deployment.
Our co-founders Xerxes and Philip are passionate about empowering our partners in the fast approaching world of physical AI and robotics. We are a small, fast growing team who hail from Anduril, Tesla, Uber, and the U.S. Special Forces.
The RoleSpecter is hiring a perception AI engineer responsible for turning sensor data pipelines into actionable insights for our customers.
Responsibilities:
  • Implementing and deploying a variety of deep-learning based vision, vision-language, and large language models to our world-class distributed perception system
  • Building and scaling a production-grade data-collection, labelling, and model re-training platform
  • Driving the design behind a multimodal software user interface

Qualifications:
  • 5+ years of experience training, implementing, and deploying deep-learning based computer vision models in tasks such as object detection, semantic segmentation, object tracking, etc. (both single and multi-frame) in frameworks such as PyTorch, TensorRT, and ONNX
  • Experience fine-tuning, implementing, and deploying vision-language models and large language models in frameworks such as PyTorch, TensorRT-LLM, and ONNX
  • Experience optimizing model runtimes utilizing techniques such as quantization, pruning, low-rank adaptation, etc. where appropriate
  • Experience building production-grade RAG pipelines, and scaling vector databases in production
  • Strong experience in C++/Rust development in embedded systems and knowledge of Linux fundamentals
  • Strong knowledge of CUDA fundamentals
  • Experience with image/video processing, filtering, and enhancement. Knowledge of various video codecs desirable.
  • Experience with variety of sensor types such as EO and IR cameras
  • Familiarity with Rust (or ability to come up the curve quickly!)

Apply