Gen AI Data scientist - CV Applications
Gen AI Data scientist - CV Applications
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
he Video Perception team is responsible for developing cutting-edge solutions for Advanced Driver Assistance Systems (ADAS). Our team is responsible for developing end-to-end solutions by leveraging the latest advancements in the field of computer vision/deep learning.
Our goal is to drive the future of autonomous driving systems by providing reliable high-performance video perception systems.
Key Responsibilities:
Demonstrate a comprehensive understanding of contemporary Large Language Models (LLMs) including their underlying architectures and a proven ability to identify and apply them to diverse business use cases Fine-tune state-of-the-art LLMs using techniques like LoRA or other parameter-efficient fine-tuning strategies.
Deploy fine-tuned or custom LLMs on Azure ensuring scalability reliability and compliance.
Design develop and implement advanced agentic workflows and Retrieval-Augmented Generation (RAG) pipelines to enhance the reasoning and knowledge capabilities of LLM-based systems Build end-to-end ML workflows using Azure Machine Learning Studio and other Azure services. Monitor and optimize model performance post-deployment.
Collaborate with Data Scientists ML Engineers and Product Managers to integrate models into production systems.
Communicate technical concepts and findings effectively across stakeholders including non-technical teams.
Requirements :
Strong technical background: At least a Bachelors/Master of Engineering in Computer Science or Electrical Sciences or related areas with 4 years of industry experience in designing and implementing vision-based algorithms prior knowledge of working with deep neural networks is a strong plus.
Skilled software engineer with experience in Python/C coupled with strong problem-solving skills.
Passionate about solving real-world problems: Ideally worked on autonomous driving systems before.
A team player: You take ownership and work with the team to deliver exceptional results. Ability to build and iterate quickly (AGILE mindset).
You enjoy working in a fast-paced environment and you are comfortable in all stages of a product development cycle.
Good hands on: You like working with production grade machine learning pipelines from dataset curation all the way till training validation & deployment.
Good communication skills: You are able to explain technical solutions clearly to all stakeholders. You have experience writing clear concise and detailed documentation.
Skills Proficient in Python with experience in writing modular scalable and testable code.
Strong hands-on experience with Azure including services like Azure ML Studio Azure Functions Azure Container Instances etc.
Experience with fine-tuning LLMs especially using LoRA or similar parameter-efficient methods.
Demonstrated ability to deploy and operationalize LLMs in production environments on Azure.
Familiarity with the latest advancements in LLMs including ChatGPT and other open or frontier models.
Excellent communication skills with the ability to explain complex technical concepts clearly to a range of audiences.
Experience working in collaborative cross-functional teams and gathering technical requirements Data: Visualization Data preparation Data handling Data analysis & deriving insights Model frameworks: Tensorflow & PyTorch
Nice to Have: Prior experience working with Ray clusters or other distributed computing frameworks.
Experience building scalable production-grade ML pipelines.
Familiarity with Terraform and Kubernetes for infrastructure-as-code and orchestration
Understanding of MLOps best practices.
Good knowledge in Deep Learning : Computer vision (object detection segmentation depth estimation) Supervised & Self-supervised learning & Transfer Learning CNNs Data augmentation and annotation Scene understan
Qualifications :
B.E
Additional Information :
Exp- 4 years
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
