Manager - PD (Arch GenAI_Mgr)

Description

Roles & responsibilities

Here are some of the key responsibilities of manager in Gen AI and ML Specialist : 

1. Team Management: You will be responsible for managing a team of AI and ML specialists, providing guidance, support, and mentoring to ensure their professional growth and development.

2. Project Management: You will oversee the planning, execution, and delivery of AI and ML projects, ensuring that they are completed within budget and timeline constraints. This includes defining project goals, allocating resources, and managing risks.

3. Strategy Development: You will collaborate with senior management to define the AI and ML strategy for the organization, identifying areas where AI and ML technologies can be applied to drive business growth and efficiency.

4. Technical Expertise: As a manager, you should have a deep understanding of AI and ML technologies, algorithms, and frameworks. You will provide technical guidance to your team, review their work, and ensure that the best practices and industry standards are followed.

5. Stakeholder Management: You will collaborate with various stakeholders, such as business leaders, product managers, and data scientists, to understand their requirements and translate them into AI and ML solutions. Effective communication and relationship-building skills are crucial for successful stakeholder management.

6. Talent Acquisition: You may be involved in the recruitment and hiring process, identifying and attracting top AI and ML talent to join your team. This includes conducting interviews, evaluating candidates' technical skills, and assessing their fit within the organization.

7. Continuous Learning: AI and ML technologies are rapidly evolving fields, and as a manager, you should stay updated with the latest advancements and industry trends. You should encourage continuous learning within your team and promote a culture of innovation and knowledge sharing.

8. Performance Evaluation: You will be responsible for evaluating the performance of your team members, providing constructive feedback, and identifying areas for improvement. You may also be involved in performance appraisals and career development discussions.

9. Collaboration and Cross-functional Coordination: AI and ML projects often require collaboration with other teams, such as data engineering, software development, and business analytics. You will need to coordinate with these teams to ensure smooth integration and deployment of AI and ML solutions.

10. Ethics and Compliance: AI and ML technologies raise ethical and legal considerations. As a manager, you should ensure that your team adheres to ethical guidelines and complies with relevant regulations, such as data privacy and security laws.

Overall, your role as a Gen AI and ML Specialist Manager is to lead and guide your team in leveraging AI and ML technologies to solve complex problems, drive innovation, and deliver value to the organization.

Mandatory  technical & functional skills

•The ideal candidate will have a strong background in natural language processing (NLP), Gen AI, deep learning, and machine learning.

•This role will be instrumental in designing, developing, and implementing AI models for a variety of generative tasks, working in a cross-functional team.

•Proficiency in Python or R and machine learning frameworks like TensorFlow or PyTorch is crucial.

•Cloud computing experience, particularly with Google/Azure Cloud Platform, is essential. With strong foundation in understating Data Analytics Services offered by Azure (Synapse)

•In depth knowledge on ML and NLP algorithms, LLMs ( BERT, GEPT, etc.) and also hands-on LangChain/LangGraph/LangSmith or LlamaIndex or LlamaCloud, OpenAI LLM Libraries,  Vector DBs (Chroma DB, FAISS, etc)

•Strong oral and written communication skills with the ability to communicate technical and non-technical concepts to peers and stakeholders

Preferred technical & functional skills

•Experience in solutioning and delivering enterprise level AI/ML projects

•Large scale deployment of ML projects, with good understanding of DevOps /MLOps /LLM Ops

•Training and fine tuning of Large Language Models (PALM2, GPT4, LLAMA etc ) or SLM's

Key behavioral attributes/requirements

•Ability to mentor junior developers

•Ability to own project deliverables, not just individual tasks

•Understand business objectives and functions to support data needs

#KGS

#LI-SS1

Responsibilities

Roles & responsibilities

Here are some of the key responsibilities of manager in Gen AI and ML Specialist : 

1. Team Management: You will be responsible for managing a team of AI and ML specialists, providing guidance, support, and mentoring to ensure their professional growth and development.

2. Project Management: You will oversee the planning, execution, and delivery of AI and ML projects, ensuring that they are completed within budget and timeline constraints. This includes defining project goals, allocating resources, and managing risks.

3. Strategy Development: You will collaborate with senior management to define the AI and ML strategy for the organization, identifying areas where AI and ML technologies can be applied to drive business growth and efficiency.

4. Technical Expertise: As a manager, you should have a deep understanding of AI and ML technologies, algorithms, and frameworks. You will provide technical guidance to your team, review their work, and ensure that the best practices and industry standards are followed.

5. Stakeholder Management: You will collaborate with various stakeholders, such as business leaders, product managers, and data scientists, to understand their requirements and translate them into AI and ML solutions. Effective communication and relationship-building skills are crucial for successful stakeholder management.

6. Talent Acquisition: You may be involved in the recruitment and hiring process, identifying and attracting top AI and ML talent to join your team. This includes conducting interviews, evaluating candidates' technical skills, and assessing their fit within the organization.

7. Continuous Learning: AI and ML technologies are rapidly evolving fields, and as a manager, you should stay updated with the latest advancements and industry trends. You should encourage continuous learning within your team and promote a culture of innovation and knowledge sharing.

8. Performance Evaluation: You will be responsible for evaluating the performance of your team members, providing constructive feedback, and identifying areas for improvement. You may also be involved in performance appraisals and career development discussions.

9. Collaboration and Cross-functional Coordination: AI and ML projects often require collaboration with other teams, such as data engineering, software development, and business analytics. You will need to coordinate with these teams to ensure smooth integration and deployment of AI and ML solutions.

10. Ethics and Compliance: AI and ML technologies raise ethical and legal considerations. As a manager, you should ensure that your team adheres to ethical guidelines and complies with relevant regulations, such as data privacy and security laws.

Overall, your role as a Gen AI and ML Specialist Manager is to lead and guide your team in leveraging AI and ML technologies to solve complex problems, drive innovation, and deliver value to the organization.

Mandatory  technical & functional skills

•The ideal candidate will have a strong background in natural language processing (NLP), Gen AI, deep learning, and machine learning.
•This role will be instrumental in designing, developing, and implementing AI models for a variety of generative tasks, working in a cross-functional team.
•Proficiency in Python or R and machine learning frameworks like TensorFlow or PyTorch is crucial.
•Cloud computing experience, particularly with Google/Azure Cloud Platform, is essential. With strong foundation in understating Data Analytics Services offered by Azure (Synapse)
•In depth knowledge on ML and NLP algorithms, LLMs ( BERT, GEPT, etc.) and also hands-on LangChain/LangGraph/LangSmith or LlamaIndex or LlamaCloud, OpenAI LLM Libraries,  Vector DBs (Chroma DB, FAISS, etc)
•Strong oral and written communication skills with the ability to communicate technical and non-technical concepts to peers and stakeholders

Preferred technical & functional skills

•Experience in solutioning and delivering enterprise level AI/ML projects
•Large scale deployment of ML projects, with good understanding of DevOps /MLOps /LLM Ops
•Training and fine tuning of Large Language Models (PALM2, GPT4, LLAMA etc ) or SLM's

Key behavioral attributes/requirements

•Ability to mentor junior developers
•Ability to own project deliverables, not just individual tasks
•Understand business objectives and functions to support data needs  

#KGS

#LI-SS1

Qualifications

This role is for you if you have  the below

Educational qualifications

-Bachelor's degree in Computer Science

Work experience

10+ Years of Experience

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