Role And Responsibilities
You will be embedded within a team of machine learning engineers and data scientists, responsible for building and productizing generative AI and deep learning solutions.
You will:
- Design, develop and deploy production ready scalable solutions that utilizes GenAI, Traditional ML models, Data science and ETL pipelines
- Collaborate with cross-functional teams to integrate AI-driven solutions into business operations.
- Build and enhance frameworks for automation, data processing, and model deployment.
- Utilize Gen-AI tools and workflows to improve the efficiency and effectiveness of AI solutions.
- Conduct research and stay updated with the latest advancements in generative AI and related technologies.
- Deliver key product features within cloud analytics.
Requirements:
- Tech, M. Tech or PhD in computer science, electrical engineering, statistics or math.
- At least 5 years of working experience in data science, computer vision, or related domain.
- Proven experience with building and deploying generative AI solutions.
- Strong programming skills in Python and solid fundamentals in computer science, particularly in algorithms, data structures, and OOP.
- Experience with Gen-AI tools and workflows.
- Proficiency in both vision-related AI and data analysis using generative AI.
- Experience with cloud platforms and deploying models at scale.
- Experience with transformer architectures and large language models (LLMs).
- Familiarity with frameworks such as TensorFlow, PyTorch, and Hugging Face.
- Proven leadership and team management skills.
Desired skills:
- Working experience with AWS, Azure AI tools is a plus.
- Technologies such as: Kafka streams, Queues, Rest API systems.
- Programing language: Python, SQL, C++ (good to have)
- Tools: Pytorch, FastAPI, MLFlow, Hugging face pipelines, Langgraph, OpenAI
- Knowledge of best practices in software development, including version control, testing, and continuous integration
