Deep Learning Engineer at Jio Platforms Limited · Navi Mumbai, Mumbai · 3 - 5 years · ₹9L - ₹15L / yr · Profitable · Posted 3 May 2023
Team:- We are a team of 9 data scientists working on Video Analytics Projects, Data Analytics projects for internal AI requirements of Reliance Industries as well for the external business. At a time, we make progress on multiple projects(atleast 4) in Video Analytics or Data Analytics.

About Jio Platforms Limited
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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
AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.
Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)
Responsibilities:
- Own the full ML lifecycle: model design, training, evaluation, deployment
- Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
- Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
- Build agentic workflows for reasoning, planning, and decision-making
- Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
- Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
- Collaborate with product and engineering teams to integrate AI models into business applications
- Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices
Requirements
- 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
- Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
- Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
- Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
- Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
- Strong software engineering background with experience in testing, version control, and APIs
- Proven ability to balance innovation with scalable deployment
- B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
- Bonus: Open-source contributions, GenAI research, or applied systems at scale
About the Role
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.
Key Responsibilities
· Design, develop, and deploy machine learning models for real-world business problems
· Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring
· Implement and manage MLOps pipelines for scalable and reproducible workflows
· Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management
· Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications
· Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions
· Optimize model performance and ensure production stability
· Stay updated with the latest advancements in AI/ML and GenAI ecosystems
Required Skills & Qualifications
· 4+ years of experience in Data Science / Machine Learning
· Strong programming skills in Python
· Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)
· Solid understanding of MLOps practices and tools
· Experience with MLflow or similar model lifecycle tools
· Practical experience in Generative AI (GenAI), including working with LLMs
· Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch
· Strong understanding of data structures, algorithms, and statistics
· Experience with cloud platforms (AWS/GCP/Azure) is a plus
Good to Have
· Experience with LLM fine-tuning, prompt engineering, or RAG pipelines
· Exposure to Docker, Kubernetes, and CI/CD pipelines
· Knowledge of data engineering workflows






