Senior AI Engineer-Computer Vision

Acesoft Labs; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Acesoft Labs in Bengaluru is seeking a Senior AI Engineer to design, train, and deploy computer vision models for edge devices. You will optimize models for edge hardware using TensorFlow, PyTorch, and ONNX, with Python and C++ and CUDA/OpenCL for performance. Strong MLOps and Git collaboration are required.

5-7 years of relevant experience and a degree in a related field are expected, along with collaboration across teams to deliver integrated AI solutions in a fast-paced environment.

Qualifications

• Education: Bachelor's or Master's in CS/EE or related field.
• 5-7 years designing, training, and deploying computer vision models.
• Expertise in model optimization (quantization, pruning, distillation, sparsity).
• Hands-on with YOLO, Faster R-CNN, Vision Transformers and deployment optimization.
• Strong CV knowledge: image preprocessing, feature extraction, and end-to-end pipelines.
• Performance profiling: inference speed, memory, throughput in constrained environments.
• Hardware optimization for embedded/low-power devices (NVIDIA Jetson, ARM, etc.).
• Proficiency in Python and C++ for AI solutions; CUDA/OpenCL for parallelism.
• MLOps familiarity: CI/CD, Docker, deployment frameworks; Git workflows.
• Collaborative, strong communication and documentation abilities.

Responsibilities

• Design, train, and deploy computer vision models.
• Optimize models for edge and low-power hardware.
• Profile and improve inference speed, memory, and throughput.
• Collaborate with cross-functional teams and stakeholders.

Skills

TensorFlow

PyTorch

ONNX

Python

C++

CUDA/OpenCL

MLOps

Git

Education

Bachelor's or Master's in CS/EE

Tools

Docker

CUDA

Git

Job description

Senior AI Engineer

Location: Bangalore (onsite). Candidates are expected to report to the office 5 days a week.

• Education: Bachelors or Masters degree in Computer Science, Electrical Engineering, or a related field.
• Experience: 5-7 years of experience in designing, training, and deploying computer vision models using frameworks like TensorFlow, PyTorch, or ONNX.
• Model Optimization: Expertise in model quantization, pruning, distillation, and structured sparsity techniques to enhance performance on edge devices and low-power hardware.
• Architectures: Hands‑on experience with state‑of‑the‑art architectures such as YOLO, Faster R-CNN, Vision Transformers, and their optimization for deployment.
• Computer Vision: Strong understanding of image preprocessing, feature extraction, traditional computer vision techniques, and end‑to‑end model pipelines.
• Performance Profiling: Experience in profiling and optimizing model inference speed, memory usage, and throughput for resource‑constrained environments.
• Hardware Optimization: Practical experience in deploying AI models on embedded systems and low‑power hardware like NVIDIA Jetson, Intel Movidius, or ARM processors.
• Programming: Proficiency in Python and C++ for developing AI solutions, with experience in parallel processing (CUDA, OpenCL) and hardware‑aware optimizations.
• MLOps: Familiarity with CI/CD pipelines, containerization (Docker), and deployment frameworks for managing AI workflows efficiently.
• Version Control: Strong experience with Git and collaborative workflows in team‑based environments.
• Soft Skills: Strong analytical thinking, communication skills, and ability to document processes effectively.
• Collaboration: Proven ability to work in cross‑functional teams, collaborate with stakeholders, and contribute to project planning.