 
						Lead Data Scientist
7 hours ago
We are currently seeking a Lead Data Scientist - Computer Vision & Generative AI to join our team in Bangalore, Karntaka (IN-KA), India (IN).
We are seeking a highly skilled and experienced Lead Data Scientist with 7+ years of expertise in Machine Learning, Deep Learning (especially Computer Vision), and Generative AI. The ideal candidate will lead the design and deployment of cutting-edge AI solutions across domains such as video intelligence, human motion analysis, and multilingual/multimodal understanding. This role involves hands-on development, team leadership, and cross-functional collaboration to drive impactful business outcomes.
Key Responsibilities
- Lead the development of computer vision systems including object detection, tracking, segmentation, and pose estimation.
- Architect and implement Generative AI solutions using LLMs and diffusion models for vision-language tasks.
- Build and optimize ML pipelines for predictive analytics, video summarization, and real-time inference.
- Collaborate with product, research, and engineering teams to align AI innovation with business goals.
- Manage sprint cycles, conduct code reviews, and mentor junior engineers.
- Deploy scalable models using Docker, Kubernetes, and CI/CD workflows.
- Automate video/audio processing using FFmpeg and integrate annotation tools.
- Ensure robust model versioning, cataloging, and lifecycle management.
Required Skills & Qualifications
- Bachelors degree in Information Technology, Computer Science, or related field.
- Proven experience in ML/DL frameworks: TensorFlow, PyTorch, Keras.
- Strong programming skills in Python, SQL, and Bash.
- Hands-on experience with GenAI tools: Falcon, LAMA, SAM, StableLM, LoRA.
- Expertise in NLP, Computer Vision, and multimodal AI.
- Familiarity with MLOps tools: Docker, Kubernetes, Airflow, Terraform.
- Experience with cloud platforms: AWS, GCP.
- Excellent communication and leadership skills.
Preferred Certifications
- Udacity Data Scientist Nanodegree
- IBM Data Science Professional Certificate (Coursera)
Nice to Have
- Experience in agricultural analytics or sports-tech applications.
- Knowledge of FFmpeg, LangChain, and vector databases (FAISS, Pinecone).
- Dashboarding experience using Streamlit or R.
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