Manager – Agentic AI

Jobtailor; Kolkata District; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Jobtailor seeks an experienced data scientist/ML leader to design and implement state-of-the-art AI solutions, including LLMs and generative AI, for enterprise use cases in India.

You will collaborate with stakeholders to define AI project goals, deploy models on cloud platforms, and integrate with APIs while ensuring data privacy and security. This role demands expertise in ML/DL, NLP, and scalable data engineering, with a focus on practical enterprise impact.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8-11 years of experience in Data Science and ML.
• Strong knowledge of ML, DL, and Generative AI techniques.
• Proficiency in Python, R, and frameworks like TensorFlow or PyTorch.
• Strong NLP knowledge with BERT, GPT, or Transformer models.
• Experience with cloud platforms (Azure, AWS, GCP) and deploying AI on cloud.
• Expertise in data curation, cleaning, and preprocessing.
• Understanding of trusted AI practices: fairness, transparency, accountability.
• Collaboration with software engineering and operations for deployment.
• Excellent problem-solving, analytical, and communication skills.
• Understanding of data privacy and ethical AI considerations.
• Track record of staying updated with AI research.

Responsibilities

• Contribute to design and implementation of state-of-the-art AI solutions.
• Assist in developing AI models and systems using LLMs and generative AI.
• Collaborate with stakeholders to define AI project goals and opportunities.
• Stay updated with advancements in generative AI techniques and applications.
• Develop innovative AI solutions for enterprise industry use cases.
• Integrate with APIs and libraries (Azure OpenAI, Hugging Face) to leverage pretrained models.
• Implement end-to-end pipelines for generative AI projects and deploy models.
• Utilize vector databases like Redis and NoSQL for large datasets and outputs.
• Apply similarity search methods for efficient information retrieval from outputs.
• Collaborate with domain experts and clients to tailor AI solutions.
• Research transfer learning, domain adaptation, and model compression to improve performance.
• Ensure data privacy, security, and ethical AI considerations.

Skills

Machine Learning

Deep Learning

Generative AI

Natural Language Processing

Data Curation

Data Cleaning

Model Deployment

Similarity Search Algorithms

Transfer Learning

Domain Adaptation

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

TensorFlow

PyTorch

Azure

AWS

GCP

Redis

Hugging Face Transformers

Job description

Responsibilities

• Contribute to the design and implementation of state-of-the-art AI solutions
• Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI
• Collaborate with stakeholders to identify business opportunities and define AI project goals
• Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges
• Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment
• Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs
• Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs
• Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly
• Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency
• Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases
• Ensure compliance with data privacy, security, and ethical considerations in AI applications
• Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Minimum 8-11 years of experience in Data Science and Machine Learning
• In-depth knowledge of machine learning, deep learning, and generative AI techniques
• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch
• Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models
• Familiarity with computer vision techniques for image recognition, object detection, or image generation
• Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment
• Expertise in data engineering, including data curation, cleaning, and preprocessing
• Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems
• Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions
• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels
• Understanding of data privacy, security, and ethical considerations in AI applications
• Track record of driving innovation and staying updated with the latest AI research and advancements

Hard Skills

• Machine Learning
• Deep Learning
• Generative AI
• Natural Language Processing
• Data Curation
• Data Cleaning
• Model Deployment
• Similarity Search Algorithms
• Transfer Learning
• Domain Adaptation

Soft Skills

• Problem-Solving
• Analytical Skills
• Collaboration
• Communication
• Interpersonal Skills