AI Engineer - Mid Level

Job highlights

• . Job Category - IT . Job Type - Full Time . No of openings: 01 .
• . Bachelors in Computer Science,Artificial Intelligence,or a related field
• Preferred Candidate Location - Telangana,Andhra Pradesh . .

AI Engineer - Mid Level

• Job Category - IT
• Job Type - Full Time
• No of openings: 01
• Experience - 4 to 6 Years
• Job Location - Hyderabad
• Preferred Candidate Location - Telangana, Andhra Pradesh

Apply

Job Overview

As an AI Engineer, you will be at the forefront of developing intelligent systems with a specialization in natural language processing (NLP). Your role involves designing, implementing, and optimizing AI models to process and Data.

As an AI Engineer specializing in NLP, your work will contribute to the development of advanced applications, including conversational AI, chatbots, Task Automation and language understanding systems. This role requires a blend of technical skills, creativity, and a commitment to staying abreast of the latest advancements in AI and NLP.

Roles & Responsibilities

Model Development:

• Design and implement state-of-the-art AI models, particularly focusing on NLP tasks, using frameworks such as PyTorch, Tensorflow, Scikit-Learn.
• Fine-tune and adapt pre-trained models to specific applications and domains.
• At least 1 Year of Experience in working with Gen AI, LLM s, Prompt Engineering, Fine tuning LLM s.
• Must have experience and contribution in developing custom models, Large language models, fine tuning LLM s and must have open source contributions.

Data Processing and Analysis:

• Preprocess and analyze large datasets to ensure high-quality input for training AI models.
• Collaborate with data engineers to build efficient pipelines for handling linguistic data.

Algorithmic Development:

• Develop algorithms for various NLP tasks, including text classification, sentiment analysis, named entity recognition, and language generation.
• Experiment with different machine learning techniques to enhance model performance.

Evaluation and Optimization:

• Implement robust evaluation metrics to assess the effectiveness of AI models.
• Optimize models for speed, memory usage, and scalability, ensuring efficient deployment in real-world applications.

Collaboration:

• Collaborate with cross-functional teams, including software engineers, data scientists, and domain experts.
• Work closely with researchers to integrate cutting-edge AI advancements into practical solutions.

Documentation and Communication:

• Maintain clear documentation for code, models, and processes.
• Communicate findings and updates to both technical and non-technical stakeholders.

Qualifications

• Bachelors in Computer Science, Artificial Intelligence, or a related field.
• Proficient programming skills in languages like Python
• Strong expertise in deep learning frameworks
• WatsonX Experience is a plus
• Solid understanding of machine learning principles, especially in the context of language models.
• Experience with large-scale data processing and distributed computing.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.

Model Development:

• Design and implement state-of-the-art AI models, particularly focusing on NLP tasks, using frameworks such as PyTorch, Tensorflow, Scikit-Learn.
• Fine-tune and adapt pre-trained models to specific applications and domains.
• At least 1 Year of Experience in working with Gen AI, LLM s, Prompt Engineering, Fine tuning LLM s.
• Must have experience and contribution in developing custom models, Large language models, fine tuning LLM s and must have open source contributions.

Data Processing and Analysis:

• Preprocess and analyze large datasets to ensure high-quality input for training AI models.
• Collaborate with data engineers to build efficient pipelines for handling linguistic data.

Algorithmic Development:

• Develop algorithms for various NLP tasks, including text classification, sentiment analysis, named entity recognition, and language generation.
• Experiment with different machine learning techniques to enhance model performance.

Evaluation and Optimization:

• Implement robust evaluation metrics to assess the effectiveness of AI models.
• Optimize models for speed, memory usage, and scalability, ensuring efficient deployment in real-world applications.

Collaboration:

• Collaborate with cross-functional teams, including software engineers, data scientists, and domain experts.
• Work closely with researchers to integrate cutting-edge AI advancements into practical solutions.

Documentation and Communication:

• Maintain clear documentation for code, models, and processes.
• Communicate findings and updates to both technical and non-technical stakeholders.

Qualifications

• Bachelors in Computer Science, Artificial Intelligence, or a related field.
• Proficient programming skills in languages like Python
• Strong expertise in deep learning frameworks
• WatsonX Experience is a plus
• Solid understanding of machine learning principles, especially in the context of language models.
• Experience with large-scale data processing and distributed computing.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.