2+ Data extraction Jobs in Hyderabad | Data extraction Job openings in Hyderabad

We seek a skilled AI Engineer with a background in AI research, machine learning, and data science to join our innovative team! This is an exciting opportunity for an individual with extensive AI experience eager to work on cutting-edge projects, turning research into practical AI applications. You will collaborate with cross-functional teams to design, develop, and implement AI solutions that enhance business operations and decision-making processes.

What We’re Looking For

● Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. A PhD in AI or a related discipline is highly desirable.

● Experience:

○ Proven experience in AI research and implementation, with a deep

understanding of both theoretical and practical aspects of AI.

○ Strong proficiency in machine learning (ML), data science, and deep learning techniques.

○ Hands-on experience with Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.

○ Experience with data preprocessing, feature engineering, and data

visualization.

○ Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI and ML deployment.

○ Strong analytical and problem-solving skills.

○ Ability to translate AI research into practical applications and solutions.

○ Knowledge of AI model evaluation techniques and performance optimization.

○ Strong communication skills for presenting research and technical details to non- technical stakeholders.

○ Ability to work independently and in team environments.

Preferred Qualifications

● Experience working with natural language processing (NLP), computer vision, or reinforcement learning.

What You’ll Be Doing

● Conduct advanced AI research to develop innovative solutions for business challenges.

● Design, develop, and train machine learning models, including supervised, unsupervised, and deep learning algorithms.

● Collaborate with data scientists to analyze large datasets, identify patterns, and extract actionable insights.

● Work with software development teams to integrate AI models into production environments.

● Leverage state-of-the-art AI tools, frameworks, and libraries to accelerate AI development.

● Optimize AI models for accuracy, performance, and scalability in real-world applications.

● Collaborate closely with cross-functional teams, including product managers, software engineers, and data scientists, to implement AI-driven solutions.

● Document AI research outcomes, development processes, and performance metrics. Present findings to stakeholders in an easily understandable manner.

What We’re Looking For

Proven experience as a Machine Learning Engineer, Data Scientist, or similar role

Expertise in applying machine learning algorithms, deep learning, and data mining techniques in an enterprise environment

Strong proficiency in Python (or other languages) and familiarity with libraries such as Scikit-learn, TensorFlow, PyTorch, or similar.

Experience working with natural language processing (NLP) or computer vision is highly desirable.

Understanding and experience with (MLOps), including model development, deployment, monitoring, and maintenance.

Experience with cloud platforms (like AWS, Google Cloud, or Azure) and knowledge of deploying machine learning models at scale.

Familiarity with data architecture, data engineering, and data pipeline tools.

Familiarity with containerization technologies such as Docker, and orchestration systems like Kubernetes.

Knowledge of the insurance sector is beneficial but not required.

Bachelor's/Master's degree in Computer Science, Data Science, Mathematics, or a related field.

What You’ll Be Doing

Algorithm Development:

Design and implement advanced machine learning algorithms tailored for our datasets.

Model Creation:

Build, train, and refine machine learning models for business integration.

Collaboration:

Partner with product managers, developers, and data scientists to align machine learning solutions with business goals.

Industry Innovation:

Stay updated with Insurtech trends and ensure our solutions remain at the forefront.

Validation:

Test algorithms for accuracy and efficiency, collaborating with the QA team.

Documentation:

Maintain clear records of algorithms and models for team reference.

Professional Growth:

Engage in continuous learning and mentor junior team members.