Join Our Trailblazing Team at Neuramonks!

Role Objective:

Generate qualified leads and schedule meetings for AI/ML services through outbound channels and freelance platforms like Upwork.

Key Responsibilities:

- Identify and research potential clients (LinkedIn, Clutch, Apollo, etc.)
- Execute outbound lead generation
- LinkedIn outreach
- Cold emailing
- Actively manage and generate leads from Upwork
- Search and identify relevant AI/ML, data, and automation projects
- Submit customised proposals
- Handle client communication and follow-ups
- Qualify leads based on the defined ICP
- Schedule meetings for the sales/closing team
- Maintain a daily activity tracker / CRM

Requirements

- 6 months – 2 years experience in lead generation / bidding.

- Hands-on experience with Upwork bidding (mandatory or strong preference)

- Basic understanding of IT services / AI/ML (preferred)

- Strong written English and proposal drafting skills

- Target-driven and self-managed

Key Responsibilities:

- Assist in the development, training, and optimization of computer vision models for various applications, including object detection, segmentation, classification, and image generation.

- Conduct research on the latest advancements in computer vision, deep learning, and image processing techniques.

- Work with image and video datasets, performing data preprocessing, augmentation, and analysis to enhance model performance.

- Implement and fine-tune state-of-the-art deep learning architectures such as CNNs (ResNet, EfficientNet), Vision Transformers (ViTs), and GANs.

- Develop and optimize vision models using frameworks like TensorFlow, PyTorch, and OpenCV.

- Utilize feature extraction, edge detection, and other classical computer vision techniques to complement deep learning models.

- Explore and implement foundation models in vision, including CLIP, DINO, SAM, and Diffusion Models, for cutting-edge applications.

- Deploy and integrate computer vision models into real-world applications, including edge devices, cloud platforms, and embedded systems.

- Collaborate with cross-functional teams to define use cases, evaluate model performance, and refine approaches for better accuracy and efficiency.

- Document research findings, model performance metrics, and key insights for internal reports and presentations.

- Stay updated with new trends in computer vision, AI, and deep learning research to incorporate innovative solutions.

Skills Required:

- Basic Knowledge of AI/ML:  Understanding of fundamental concepts in machine learning and artificial intelligence.

- Computer Vision Fundamentals: Strong understanding of image processing, feature extraction, and object recognition.

- Programming Skills: Proficiency in Python; experience with libraries such as OpenCV, TensorFlow, PyTorch, and scikit-image is a plus.

- Deep Learning Models: Familiarity with CNNs, Vision Transformers, and generative models for tasks like object detection (YOLO, Faster R-CNN), segmentation (UNet, SAM), and image synthesis (GANs, Diffusion Models).

- Data Handling & Preprocessing: Experience in handling large-scale image/video datasets using NumPy, Pandas, and OpenCV for data augmentation and transformation.

- Mathematical Proficiency: Understanding of linear algebra, probability, and optimization techniques relevant to computer vision and AI.

- Model Optimization: Experience in techniques such as pruning, quantization, and knowledge distillation to enhance model efficiency.

- Deployment & Integration: Understanding of model deployment on cloud (AWS, GCP) and edge devices (TensorRT, OpenVINO, TFLite).

- Problem-Solving Abilities: Strong analytical thinking and debugging skills to handle real-world vision challenges.

- Team Collaboration: Good communication skills and the ability to work effectively in a team environment.

- Eagerness to Learn: A passion for AI, deep learning, and computer vision, with a drive to stay updated with the latest research and industry advancements.