Robotics Computer Vision Engineer Job at Formic (San Francisco)

Senior Machine Learning Engineer, Computer Vision - Robotics

Scale’s Robotics business unit is dedicated to solving the data bottleneck in Ph...

Location

United States , San Francisco

Salary:

218400.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Ph.D. in Computer Science, Computer Engineering, or a related quantitative field (Mathematics, Electrical Engineering, etc.) OR a Master’s degree with 4+ years of equivalent professional experience in an applied research setting
5+ years of hands-on experience in algorithm development for 2D/3D computer vision and deep learning
Expert proficiency in at least one major deep learning framework (PyTorch, TensorFlow or Jax)
Mastery of Python for machine learning and strong proficiency in C++ for performance-critical algorithm implementation
In-depth knowledge of classical and modern computer vision fundamentals, including multi-view geometry, projective geometry, camera calibration, and 3D graphics/rendering principles
Building real-time and batch ML systems that analyze structured and unstructured signals
Hands-on experience rapidly prototyping and iterating on ML systems with changing requirements

Job Responsibility

Pioneer Core CV Algorithms: Lead the research, design, and implementation of novel computer vision and deep learning algorithms, with a specialized focus on 2D and 3D data (e.g point clouds)
Focus Area Expertise: Drive innovation in key perception areas, including: 3D Reconstruction and SLAM: Advanced techniques for real-time 3D mapping, pose estimation, and environmental modeling from multi-modal sensor inputs (e.g., RGB-D, LiDAR). Hand/Body Tracking: Developing robust and precise models for hand pose estimation, gesture recognition, and full-body tracking under various lighting and occlusion conditions. Object Detection and Tracking (MOT/SOT): Designing high-performance deep learning models for accurate detection and persistent tracking of objects and people in video streams. Video Processing: Creating algorithms for temporal feature extraction, video-based action recognition, and motion analysis
Model Optimization: Optimize computationally intensive models for deployment on edge devices (low power, low latency) and/or large-scale cloud infrastructure
Technical Leadership: Serve as the subject matter expert in Computer Vision, providing technical direction and mentorship to junior engineers and cross-functional teams
Publication & IP: Maintain state-of-the-art knowledge, evaluate recent academic publications (e.g., CVPR, ICCV, ECCV), and drive the filing of patents and publication of novel research
Cross-Functional Partnering: Collaborate closely with Software Engineering, Product, and Hardware teams to define requirements, integrate vision systems, and ensure solutions meet performance targets

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
equity based compensation
may be eligible for additional benefits such as a commuter stipend

Fulltime

Research Engineer - Computer Vision and Robotics

The Surreal Team at Meta’s Reality Lab Research is a multi-disciplinary, vertica...

Location

United States , Redmond

Salary:

181000.00 USD / Year ▼

Computer Vision Engineer, Reality Labs

The Reality Labs organization is helping more people around the world come toget...

Location

United States of America , Redmond

Salary:

154003.00 - 217000.00 USD / Year

Computer Vision Engineer

We are seeking a Computer Vision Architect to lead the design and implementation...

Location

United States , Los Angeles

Salary:

140000.00 - 220000.00 USD / Year

Snail Games

Expiration Date

Until further notice

Requirements

5+ years of professional experience in computer vision, real-time perception, or related fields
Advanced degree (Master’s or PhD) in AI, Computer Vision, Robotics, or related field preferred
Proven experience building and deploying real-time video perception systems in production environments
Strong C++ proficiency and experience integrating systems into game engines or comparable real-time platforms
Deep understanding of object detection, tracking, temporal modeling, and 3D scene understanding
Experience optimizing models for deployment using CUDA, TensorRT, ONNX, or similar toolchains
Unreal Engine Experience: Proficiency with Unreal Engine, preferably UE4 or UE5

Job Responsibility

Architect and implement real-time computer vision pipelines for analyzing gameplay video and camera feeds
Design systems that convert 2D visual input into structured 3D semantic world models usable by AI agents and NPC systems
Integrate perception modules into Unreal Engine–based runtimes and toolchains
Optimize inference performance for GPU-constrained, real-time environments
Define data collection, evaluation, and iteration strategies for improving perception robustness
Collaborate with AI engineers to design perception interfaces that feed behavior trees, agent systems, and decision models
Establish long-term technical direction for vision-driven gameplay and simulation features

What we offer

True focus on work/life balance
Paid company holidays, vacation, and separate sick leave
Medical, dental, vision, and Life/LTD
401k with company match

Fulltime

Computer Vision Engineer

Location

India , Bengaluru

Salary:

Not provided

Larsen & Toubro

Expiration Date

August 12, 2026

Requirements

Bachelor’s degree in Robotics, Computer Science, Mechatronics or related field
Strong proficiency in modern C++ (14/17/20) and Python
Deep understanding of computer vision fundamentals (feature-based vision, geometric methods, multi-view geometry) and AI-based perception using PyTorch
Practical experience deploying and optimising perception models on embedded GPU platforms (Jetson Xavier/Orin or similar)
Hands-on expertise with Triton, TensorRT, mixed-precision inference, Numba-JIT, CUDA kernels, and real-time optimisation techniques
Strong command of ROS/ROS2, TF transforms, message passing, node graph architecture, and middleware integration patterns
Extensive experience with robotics sensor integration including RGB/stereo/depth cameras, LiDAR, radar, IMUs, and GPS—covering calibration (intrinsic/extrinsic), synchronization, timestamps, and data integrity
Knowledge of core autonomy concepts: mapping, costmap generation, scene representation, obstacle detection, and planner interfacing
Solid grounding in Linux systems, multithreading, memory optimisation, real-time constraints, and system-level debugging workflows
Experience with Docker, cross-compilation toolchains, embedded deployment pipelines, and CI/CD systems for robotics software

Job Responsibility

Design, implement, and maintain core autonomy modules that integrate sensing, perception, state estimation, mapping, and planner interfaces into a cohesive real-time system
Develop high-performance computer vision pipelines (classical + AI-based) for detection, segmentation, tracking, and scene understanding, ensuring reliable operation on embedded hardware
Build multimodal perception systems that fuse camera, LiDAR, radar, and IMU data into accurate, navigation-ready environment representations
Deploy, optimize, and maintain autonomy software on embedded platforms (Jetson AGX/Orin), including TensorRT optimisation, cross-compilation, CUDA acceleration, and performance tuning for real-time execution
Own sensor bring-up, configuration, calibration, and synchronization (camera, LiDAR, radar, IMU, GPS), ensuring accurate and stable data for downstream modules
Ensure system-level robustness and safety by maintaining strict latency budgets, deterministic behaviour, numerical stability, and fall-back mechanisms for degraded sensing conditions
Conduct field trials, capture datasets, analyse system performance, and drive iterative improvements across sensing, perception, fusion, and planning layers
Debug deep autonomy stack issues including timing mismatches, calibration drift, concurrency conflicts, synchronization faults, and hardware–software integration challenges
Build deployment-ready autonomy systems using ROS/ROS2, Docker, systemd services, and reproducible build pipelines tailored for embedded platforms
Collaborate with mechanical, electronics, and systems teams to align autonomy software capabilities with real-world hardware constraints and vehicle dynamics

Early-career Applications Engineer – Robotics & Vision

Exceptional early-career opportunity to grow with an industry leader in robotics...

Location

United States

Salary:

Not provided

Nondestructive & Visual Inspection

Expiration Date

Until further notice

Requirements

B. S. in Electrical, Mechatronics, Computer, or related Engineering field
0–3 years of relevant experience through work, internship, or academic projects
Strong programming fundamentals and mechanical/electrical aptitude
Curiosity, initiative, excellent communication and customer-facing skills
Willingness to travel 20–50% across the U.S.

Job Responsibility

Work directly with machine builders, system integrators, and key accounts, helping them apply cutting-edge robotics, vision, and control technologies to solve high-value industrial challenges

What we offer

Base + Bonus + Comprehensive Benefits
training, mentorship, and career advancement built into the role

Research Engineer, Computer Vision & AI

The Surreal Spatial AI group is seeking high-performing research engineers to bu...

Location

United Kingdom , London

Salary:

Not provided

Senior Computer Vision Machine Learning Engineer

Careers/codvo Engineering Senior Computer Vision Machine Learning Engineer Pune,...

Location

India , Pune

Salary:

Not provided

Codvo AI

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field
5+ years of experience in Computer Vision and Machine Learning (deep learning emphasis)
Proficiency in Python, C++, TensorFlow, PyTorch
Strong understanding of model optimization techniques for edge deployment
Hands-on experience with NVIDIA platforms – IGX, Jetson, or Xavier (IGX Orin highly preferred)
Experience with NVIDIA SDKs (e.g., DeepStream, TensorRT, CUDA, TAO Toolkit)
Solid knowledge of vision tasks: object detection, tracking, classification, segmentation
Familiarity with containerization (Docker), CI/CD pipelines, and version control (Git)

Job Responsibility

Lead the design, development, and deployment of end-to-end computer vision and deep learning models
Optimize and deploy CV/ML pipelines on edge platforms, particularly NVIDIA IGX (Orin preferred)
Work with cross-functional teams to integrate models into real-time applications (e.g., robotics, safety systems, industrial inspection)
Develop and maintain datasets, perform data augmentation, and ensure quality training inputs
Leverage NVIDIA SDKs (e.g., DeepStream, TensorRT, TAO Toolkit, CUDA) for performance and acceleration
Collaborate with hardware engineers to fine-tune models for power, latency, and throughput constraints
Stay up to date with the latest research and techniques in computer vision, edge AI, and embedded ML

What we offer

Opportunity to work on cutting-edge AI/edge technology with real-world impact
Collaborative and fast-paced engineering culture
Flexible working hours and remote work options
Competitive salary and benefits package

Fulltime

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Robotics Computer Vision Engineer

Job Description

Job Responsibility

Requirements

What we offer

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