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Machine Learning Object Detection Jobs in Massachusetts

Eka

Machine Learning / Computer Vision Engineer

Boston, MA · On-site

$90 - $130/hr

Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D ... Practical experience with visual representation learning, object detection, segmentation, pose ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global ... Evaluate and implement state-of-the-art techniques in deep learning, object detection, and visual ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Xforia, Inc.

Principal AI/ML Engineer

Boston, MA · On-site

Ensuring that all departments understand the work of the machine learning team and how it aligns ... You have expertise in radar signal processing and object detection from RF signals, including ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Sierra Ventures

Machine Learning Engineer

Somerville, MA · On-site

$170 - $200/hr

Our products help detect harm, prevent fraud, and build safer, more trusted online and real-world ... We're looking for a Senior Machine Learning Engineer to help advance the state of voice ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

... modern machine learning approaches for image analysis, including convolutional neural networks and vision transformers * Proven experience developing semantic segmentation, object detection ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

... modern machine learning approaches for image analysis, including convolutional neural networks and vision transformers * Proven experience developing semantic segmentation, object detection ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

... modern machine learning approaches for image analysis, including convolutional neural networks and vision transformers * Proven experience developing semantic segmentation, object detection ...

Varsity Tutors

Machine Learning Tutor

Newton, MA · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Cambridge, MA · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

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Machine Learning Object Detection information

What is machine learning object detection?

Machine learning object detection is a field within artificial intelligence that focuses on identifying and locating objects within images or videos. It uses algorithms and deep learning models, such as convolutional neural networks (CNNs), to analyze visual data and predict the presence and position of various objects. Object detection is widely used in applications like autonomous vehicles, security surveillance, and image search. The process typically involves training models on labeled datasets so they can accurately detect and classify multiple objects in complex scenes.

What are some common challenges faced when working on machine learning object detection projects?

One of the main challenges in machine learning object detection roles is dealing with the quality and quantity of annotated data, as accurate labeling is essential for model performance. Another common challenge is managing variations in object scale, lighting, and occlusion within real-world images, which can affect detection accuracy. Additionally, balancing model accuracy with computational efficiency—especially for real-time applications—often requires careful model selection and optimization. Collaboration with data engineers and domain experts is also typical to ensure data relevance and model applicability.

What are the key skills and qualifications needed to thrive as a machine learning object detection engineer, and why are they important?

To excel as a Machine Learning Object Detection Engineer, you need a solid background in computer science, mathematics, and deep learning principles, often backed by a relevant degree and experience in computer vision. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience with annotation tools and GPU computing, is typically required. Strong problem-solving abilities, attention to detail, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex challenges. These competencies ensure accurate model development, efficient deployment, and continual improvement of object detection systems in real-world applications.

What are popular job titles related to Machine Learning Object Detection jobs in Massachusetts?

For Machine Learning Object Detection jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Machine Learning Object Detection jobs in Massachusetts look for?

The top searched job categories for Machine Learning Object Detection jobs in Massachusetts are:

Machine Learning Object Detection jobs near you

Machine Learning / Computer Vision Engineer

Eka

Boston, MA • On-site

$90 - $130/hr

Other

Posted 13 days ago

Job description

Eka Robotics

Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable. Our approach, grounded in physics, unlocks superhuman capabilities. We are defining the frontier of robotics research and deployment.

Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D effort. We are looking for hands‑on individuals who are excited to help shape the future of robotics.

Responsibilities
  • Build computer vision and visual representation learning pipelines for robotic manipulation, including RGB, RGB‑D, depth, segmentation, pose, keypoint, and object‑centric representations.
  • Develop visual models that support reinforcement learning and imitation learning policies, including end‑to‑end visuomotor policies that map visual observations to robot actions.
  • Improve our data pipeline for vision‑based manipulation policies through domain randomization, photorealistic rendering, synthetic data generation, sensor noise modeling, and real‑world fine‑tuning.
  • Design and train perception models that are robust to lighting changes, camera viewpoint shifts, texture variation, clutter, occlusion, object instance variation, and imperfect calibration.
  • Evaluate learned visual representations and policies on real robotic manipulation tasks, identify failure modes, and iterate on models, data, and training procedures.
  • Collaborate with robotics, robot learning, and simulation engineers to define the perception strategy for robotic manipulation.
  • Set up, calibrate, and evaluate camera and depth sensing systems when needed, with an emphasis on how sensor choices affect learned policies and real‑world robustness.
Minimum Qualifications
  • Ph.D. in computer vision or 3+ years of experience working on a computer vision product.
  • Strong background in machine learning for computer vision, especially deep learning‑based visual perception.
  • Experience training modern computer vision models in JAX, PyTorch or similar frameworks.
  • Practical experience with visual representation learning, object detection, segmentation, pose estimation, depth estimation, tracking, or 3D perception.
  • Strong Python programming skills.
  • Ability to move fluidly between research code and production‑quality systems.
  • Strong understanding of how data distribution, sensor noise, calibration, lighting, and scene variation affect model performance.
Preferred Qualifications
  • Experience training policies from visual observations, including RGB, RGB‑D, point clouds, object‑centric representations, or learned latent representations.
  • Experience with domain randomization, synthetic data generation, differentiable rendering, neural rendering, or photorealistic simulation.
  • Experience with robotics simulators or synthetic data tools such as Isaac Sim, MuJoCo or similar environments.
  • Familiarity with robot learning methods such as reinforcement learning, behavior cloning, diffusion policies, offline RL, or learning from demonstrations.
  • Experience with real robot deployment, including camera calibration, hand‑eye calibration, depth sensors, ROS/ROS2, or robot data collection pipelines.
  • First‑author publications in top computer vision, robotics, or machine learning venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, RSS, CoRL, ICRA, or IROS.
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