Join Skild AI as a Computer Vision AI & ML Engineer to develop advanced perception systems for robotics and automation.
Posted by employer 4 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 day ago
Skills & Technologies
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
The Computer Vision AI & ML Engineer at Skild AI focuses on developing and deploying advanced perception systems for robotics, engaging in the entire machine learning lifecycle from model development to production integration. Key skills include expertise in deep learning frameworks like PyTorch or TensorFlow, along with a solid background in computer vision tasks such as object detection and 3D scene understanding. This role is ideal for individuals with a strong technical foundation and a passion for innovative problem-solving, regardless of their level of experience. Skild AI fosters a collaborative environment where team members can influence architectural decisions and contribute to gro
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Skild AI's careers page October 27, 2026.
- This exact title is also open at 1 other location at Skild AI: Bengaluru, India.
- Python appears in 47.7% of 822 comparable mid ai/ml roles; 3D Geometry appears in 0.1% of 822 comparable mid ai/ml roles.
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: 3D Geometry, Blender, C++, Gazebo, Isaac Sim, JAX.
- What seniority level is this role?
- Skild AI targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Computer Vision AI & ML Engineer role at Skild AI.
From the original posting
Company Overview
Position Overview
We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for real-world robotics and automation. You will work across the full machine learning lifecycle—model development, data strategy, evaluation, and production integration—to deliver robust, high-performance vision capabilities. This role combines applied research with hands-on engineering and offers the opportunity to influence both architecture and roadmap decisions.
Responsibilities
- Develop and optimize deep learning models for depth estimation, object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
- Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
- Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
- Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
- Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
- Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.
Preferred Qualifications
- Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Background in computer vision tasks such as detection, depth estimation, segmentation, tracking, or 3D scene understanding.
- Proficiency in Python; familiarity with C++ is a plus.
- Experience building training pipelines, evaluation frameworks, and ML deployment workflows.
- Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
- Experience with data annotation tools, dataset management, and augmentation techniques.
- Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
- Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.
Standard company text repeated across Skild AI's postings is omitted here.
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