RapinnoTech Solutions - Generative AI Engineer - Machine Learning (3-5 yrs)

About the Role :

We are looking for a talented and experienced Machine Learning Engineer with expertise in Generative AI and AWS Cloud to join our team. In this role, you will leverage your knowledge of large language models (LLMs), supervised learning algorithms, and machine learning techniques to develop and deploy cutting-edge solutions. You will be responsible for designing, building, and optimizing models on AWS Bedrock while collaborating with data scientists, engineers, and stakeholders to drive AI innovation across the company.

Key Responsibilities :

- Design, develop, and deploy machine learning models with a focus on Generative AI and large language models (LLMs).

- Implement and optimize supervised learning algorithms, including regression models and support vector machines (SVMs).

- Collaborate with cross-functional teams to understand business problems and propose AI-driven solutions.

- Work hands-on with AWS Bedrock to build and scale AI models and solutions.

- Utilize your expertise in Python to write clean, efficient, and well-documented code.

- Build and maintain end-to-end machine learning pipelines, from data collection to model deployment.

- Continuously improve the performance and scalability of AI models in production environments.

- Stay up to date with the latest advancements in AI, machine learning, and cloud technologies.

- Troubleshoot and resolve technical issues related to the deployment and maintenance of machine learning models.

- Contribute to the design and implementation of cloud-based ML architecture, specifically leveraging AWS cloud services.

Required Skills & Qualifications :

Generative AI : Deep understanding of Generative AI techniques, including but not limited to LLMs (Large Language Models).

Machine Learning : Strong background in supervised learning, regression, and SVM (Support Vector Machine) analysis.

Cloud Computing : Hands-on experience working with AWS cloud services, specifically AWS Bedrock for building and managing large AI models.

Programming Languages : Expertise in Python, including libraries such as TensorFlow, PyTorch, Scikit-learn, and others relevant to AI/ML development.

Data Science : Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques.

Deployment : Experience with model deployment, CI/CD pipelines, and maintaining production-grade AI systems.

Communication : Strong ability to communicate complex technical concepts to both technical and non-technical stakeholders.

Collaboration : Ability to work in a fast-paced, collaborative team environment.

Preferred Qualifications :

- Experience working with AWS Machine Learning Services (e.g., SageMaker, Lambda, etc.).

- Experience with natural language processing (NLP) techniques and applications.

- Familiarity with version control systems like Git.

- Experience with distributed computing frameworks like Apache Spark or Hadoop is a plus.