Data Scientist at Yottaasys AI LLC · Bengaluru (Bangalore) · 1 - 5 years · ₹6L - ₹15L / yr · Raised funding · Posted 20 Sep 2021
Develop state of the art algorithms in the fields of Computer Vision, Machine Learning and Deep Learning.
Provide software specifications and production code on time to meet project milestones Qualifications
BE or Master with 3+ years of experience
Must have Prior knowledge and experience in Image processing and Video processing • Should have knowledge of object detection and recognition
Must have experience in feature extraction, segmentation and classification of the image
Face detection, alignment, recognition, tracking & attribute recognition
Excellent Understanding and project/job experience in Machine learning, particularly in areas of Deep Learning – CNN, RNN, TENSORFLOW, KERAS etc.
Real world expertise in deep learning- applied to Computer Vision problems • Strong foundation in Mathematics
Strong development skills in Python
Must have worked upon Vision and deep learning libraries and frameworks such as Opencv, Tensorflow, Pytorch, keras
Quick learner of new technologies
Ability to work independently as well as part of a team
Knowledge of working closely with Version Control(GIT)

Similar jobs (4)
Position: Computer Vision Engineer
Experience: 2–3 Years
Location: Bengaluru, Karnataka
Employment Type: Full-time
About the Role
We are seeking a highly motivated Computer Vision Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating computer vision models and algorithms and pipelines for UAVs operating in both GNSS-available and GNSS-denied environments.
The ideal candidate should have a strong foundation in theory of deep learning and machine learning, strong understanding of electromagnetic spectrum, imaging fundamentals, camera principles, and mathematical concepts with hands-on experience in implementing these algorithms on embedded or real-time systems.
Key Responsibilities
- Design, develop, and optimise AI Models
- Make custom CNNs/ modify existing CNNs to suit specific problems at hand
- Handle end-to-end training flow
- Implement end to end inference pipelines on standard PCs as well as on embedded systems
- Understand performance benchmarks and assess the accuracy and inference times
- Implement traditional image processing algorithms
- Factor the code to leverage underlying hardware architecture
- Prune the networks for efficiency
- Integrate the system within the application framework using C++
- Work closely with perception, controls, embedded software, and systems engineering teams.
Required Qualifications
- B.E./B.Tech/M.E./M.Tech in Computer Science and Engineering, Electronics, ECE, Mechatronics, or a related discipline.
- 2–3 years of experience in relevant area
- Strong understanding of: Linear Algebra, Probability and Statistics, AI-ML-DL fundamentals, Image processing, Camera Functioning
- Strong programming skills in C++ and Python.
- Experience with MATLAB for algorithm development and validation.
- Familiarity with Linux development environments.
- Experience with Git version control.
Preferred Skills
- Experience with Camera, IMU Calibration and Synchronisation
- Experience with multi-sensor fusion.
- Experience working with NVIDIA devices
- Experience on FPGA will be an added advantage
- Full understanding of Git functionality
- Exposure to airborne software development processes and coding standards (e.g., MISRA C++).
Personal Attributes
- Strong analytical and problem-solving skills.
- Ability to work independently on challenging technical problems.
- Good communication and documentation skills.
- Passion for solving challenging problems
- Willingness to participate in field trials and flight testing.
- Team playwe
Hi,
Greetings !!
We/re are looking for someone who has Hands-on experience with CV/ML
The location for the same is Bangalore.
Requirements
- 11–14 years total experience
- Computer Vision – strong hands-on experience
- Object Detection – YOLO(Preferred), Faster R-CNN, SSD, etc.
- Image Processing – OpenCV, image enhancement, segmentation, feature extraction
- Machine Learning / Deep Learning – CNNs, model training, evaluation, optimization
- AI/ML – production-level AI solution development
- LLM / GenAI – practical exposure to LLMs, multimodal AI, RAG, VLMs, or GenAI
- Python – strong programming skills
- Model deployment – preferably TensorRT, ONNX, Docker, Kubernetes, cloud, or edge deployment
- Bangalore – candidate should be based in / willing to work from Bangalore
Preferred
- Vision Transformers / ViT
- YOLOv8/YOLOv9/YOLOv10/YOLO11
- PyTorch / TensorFlow
- NLP / LLM / VLM
- Generative AI
- CUDA / GPU optimization
- Edge AI / NVIDIA
- Experience leading CV/AI projects or teams
If interested, Share CV at: snigdhaattheratebeanhr.com
AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.
Implementation and testing of advanced computer vision algorithms.
Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.
Detailed analysis of results. Documentation, version control, client support, upgrades.
AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world environments.
This role focuses on building end-to-end visual intelligence systems, combining deep learning, classical computer vision techniques, and multimodal models. It is not limited to model training and requires strong ownership of system design, deployment, and real-world performance.
You will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based workflows.
You will also work on problems where existing approaches may not be sufficient, and will be expected to combine deep learning, geometric methods, and multimodal reasoning to build robust, production-grade systems.
Location – Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid – 3 days per week in office)
Responsibilities:
- Design and deploy computer vision systems for tasks such as:
- Object detection, segmentation, and tracking
- Scene understanding and structured perception
- Video understanding and temporal reasoning
- Build and optimize models using architectures such as:
- CNNs (ResNet, EfficientNet)
- Vision Transformers (ViT, Swin, DeiT)
- Detection/segmentation models (YOLO, DETR, Mask R-CNN)
- Develop multimodal systems combining vision and language:
- CLIP-style models
- Vision-language models (VLMs)
- Visual grounding and captioning systems
- Implement algorithms for:
- Multi-object tracking (SORT, DeepSORT, ByteTrack)
- Feature matching and representation learning
- Temporal modeling (RNNs, Transformers for video)
- Apply geometric and classical computer vision methods where relevant:
- Camera calibration
- Epipolar geometry
- Pose estimation
- 3D reconstruction or depth estimation
- Optimize systems for:
- Low-latency, real-time inference
- Throughput and scalability
- Edge and distributed deployment
- Design and build data pipelines for:
- Annotation workflows
- Dataset curation
- Synthetic data generation
- Integrate vision systems into:
- Multimodal AI pipelines
- Agent-based systems
- Decision-making workflows
Requirements:
- 5+ years of experience building computer vision systems in production environments
- Strong experience with deep learning frameworks (PyTorch / TensorFlow)
- Hands-on experience with:
- Detection, segmentation, or tracking systems
- Model training, fine-tuning, and evaluation
- Strong understanding of:
- Representation learning
- Loss functions (contrastive loss, focal loss, etc.)
- Evaluation metrics (mAP, IoU, precision/recall)
- Experience building and deploying end-to-end vision systems, not just training models
Candidates whose primary experience is limited to academic projects or model experimentation without real-world deployment may not be a fit for this role.
Nice to Have:
- Experience with multimodal systems (vision + language)
- Familiarity with models such as:
- CLIP, BLIP, Flamingo, or similar
- Experience with 3D vision:
- NeRFs
- SLAM
- Point clouds
- Experience with video understanding:
- Action recognition
- Event detection
- Experience building data engines:
- Active learning
- Hard negative mining
- Experience working with large-scale datasets and distributed training pipelines






