Code Driven Labs is an AI-first technology company building intelligent products that leverage Machine Learning, Computer Vision, and Large Language Models to solve real-world business problems. We develop production-grade AI systems across industries including marketing, retail, healthcare, manufacturing, and enterprise automation.
We are looking for an Applied Machine Learning / Computer Vision Engineer to join our AI team and help build our next-generation Context-Based Content Intelligence Platform. This platform analyzes images, videos, and multimedia content to understand context, quality, storytelling, branding, and audience engagement using multimodal AI.
Role Overview
As an Applied ML / CV Engineer, you will design and build AI systems capable of understanding visual and textual context rather than simply detecting objects. You will work with Vision Language Models (VLMs), Large Language Models (LLMs), computer vision pipelines, and multimodal learning techniques to generate meaningful insights from marketing and social media content.
This is a product-focused role where research is translated into scalable, production-ready AI solutions.
Key Responsibilities
- Design and develop multimodal AI models for image and video understanding.
- Build systems that analyze visual storytelling, brand consistency, scene composition, and contextual relevance.
- Develop AI pipelines that combine computer vision with natural language understanding.
- Fine-tune and evaluate Vision Language Models for custom business use cases.
- Build intelligent content scoring and recommendation engines.
- Create APIs and backend services to serve AI models in production.
- Design scalable inference pipelines for image and video processing.
- Improve model performance through experimentation, prompt engineering, fine-tuning, and model optimization.
- Work closely with product managers and software engineers to convert business requirements into AI features.
- Stay updated with the latest research in multimodal AI, computer vision, and generative AI.
Required Technical SkillsMachine Learning
- Deep Learning
- Transfer Learning
- Representation Learning
- Model Evaluation
- Feature Engineering
- Fine-tuning Foundation Models
Computer Vision
- Image Classification
- Object Detection
- Scene Understanding
- Image Embeddings
- Video Understanding
- OCR
- Image Similarity
- Visual Feature Extraction
Multimodal AI
- Vision Language Models (VLMs)
- CLIP
- SigLIP
- Florence
- BLIP
- Qwen-VL
- LLaVA
- GPT-4o or equivalent multimodal models
- Image Captioning
- Cross-modal Retrieval
Large Language Models
- Prompt Engineering
- RAG Pipelines
- Structured Output Generation
- Agentic AI Workflows
- Function Calling
- Evaluation Frameworks
Programming
AI Frameworks
- PyTorch
- Hugging Face Transformers
- OpenCV
- Ultralytics YOLO
- ONNX Runtime
- TensorRT (Preferred)
Backend
- FastAPI
- REST APIs
- Async Python
- Docker
Databases
- PostgreSQL
- Redis
- Vector Databases (FAISS, Qdrant, Pinecone, Weaviate, or Milvus)
Cloud & MLOps
- AWS, Azure, or Google Cloud
- Docker
- Git
- CI/CD
- MLflow or Weights & Biases
Preferred Experience
Experience building one or more of the following:
- AI-powered content intelligence platforms
- Social media content analysis
- Advertisement quality assessment
- Brand compliance systems
- Visual search applications
- Content recommendation engines
- Multimodal search
- Video analytics
- Marketing AI tools
- Creator or influencer analytics platforms
What You'll Build
You will contribute to AI systems capable of:
- Understanding the context and narrative of images and videos.
- Identifying products, people, logos, scenes, and activities.
- Evaluating creative quality, composition, and visual appeal.
- Assessing brand visibility and messaging consistency.
- Analyzing emotional tone and audience perception.
- Comparing content against competitors and industry benchmarks.
- Generating actionable insights and improvement recommendations.
- Powering intelligent search and retrieval using multimodal embeddings.
Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- 2–5+ years of experience in Applied Machine Learning, Computer Vision, or Multimodal AI.
- Strong understanding of deep learning and production ML systems.
- Demonstrated experience building and deploying AI applications.
Bonus Skills
- Fine-tuning open-source Vision Language Models.
- Experience with reinforcement learning from human feedback (RLHF).
- Knowledge of agentic AI frameworks.
- Experience with GPU optimization and inference acceleration.
- Familiarity with distributed model serving.
- Published AI research or notable open-source contributions.
What We're Looking For
We value engineers who:
- Are passionate about building real-world AI products.
- Stay current with advances in multimodal and generative AI.
- Can translate research papers into production-ready systems.
- Write clean, maintainable, and well-tested code.
- Thrive in a collaborative, fast-paced startup environment.
- Take ownership from concept through deployment.
Pay: ₹400,000.00 - ₹800,000.00 per year
Benefits:
Experience:
- Computer vision: 4 years (Required)
- AI: 4 years (Required)
- Machine learning: 4 years (Required)
Work Location: Remote
