We are currently seeking an Applied Machine Learning / Computer Vision Engineer to join one of our clients’ innovative AI teams.

This is an exciting opportunity to work on a next-generation AI platform combining Computer Vision, Multimodal AI, Applied Machine Learning, and Large Language Models.

Key Responsibilities

As an Applied ML / Computer Vision Engineer, you will:

- Design, develop, and improve Computer Vision and image-processing pipelines.
- Build solutions for video analysis, video understanding, and real-time visual processing.
- Develop multimodal AI systems combining vision, audio, and language data.
- Work with object detection, image segmentation, classification, tracking, and related Computer Vision techniques.
- Implement and fine-tune Vision-Language Models and Transformer-based architectures.
- Integrate Large Language Models into AI products for reasoning, analysis, and automated decision-making.
- Evaluate, optimize, and deploy machine-learning models in production environments.
- Improve model inference speed, accuracy, scalability, and resource efficiency.
- Translate research papers and emerging AI techniques into practical product features.
- Build APIs and production-grade services for AI model integration.
- Collaborate with engineering and product teams to understand business requirements and deliver effective AI solutions.
- Monitor model performance and continuously improve deployed systems.
- Maintain clear, reusable, and well-documented code.

- 1–4 years of experience in Applied Machine Learning, Computer Vision, Deep Learning, or a related field.
- Strong programming skills in Python.
- Hands-on experience with PyTorch.




- Practical knowledge of OpenCV and image or video processing.
- Strong understanding of Deep Learning fundamentals.
- Experience with object detection and/or image segmentation models.
- Knowledge of Transformer architectures.
- Experience working with Vision-Language Models.
- Familiarity with the Hugging Face ecosystem.
- Experience with model inference, evaluation, and optimization.
- Understanding of how to move models from experimentation into production.
- Experience using Docker and Git.
- Ability to independently investigate technical challenges and propose practical solutions.
- Ability to understand, reproduce, and implement methods described in research papers.

- Robust analytical and problem-solving skills.
- Curiosity and willingness to explore new technologies.
- Passion for AI, Machine Learning, and product development.
- Ownership mindset and accountability for delivered solutions.
- Ability to work independently and contribute within a team-oriented team.
- Interest in building practical products rather than focusing only on model experimentation.
- Comfortable working in a fast-moving and research-driven environment.

Nice to Have

Experience with one or more of the following technologies would be considered an advantage:

- YOLO
- GroundingDINO
- SAM or SAM2
- Florence-2
- Whisper
- Qwen2.5-VL
- LLaVA
- InternVL
- CUDA
- TensorRT
- ONNX
- FastAPI

(Exceptional fresh graduates may also be considered if they can demonstrate strong technical knowledge through relevant academic work, personal projects, GitHub repositories, Kaggle participation, research, or a technical portfolio.)

📌 Applied Machine Learning / Computer Vision Engineer (Sahibzada Ajit Singh Nagar)
🏢 TechBiz Global
📍 Sahibzada Ajit Singh Nagar