AI/ML Engineer- Software Industry Expertise (for part time mentoring)

Role Overview

AI/ML Professionals

Key Responsibilities

Agile framework system

1. Technical Mentorship & Guidance

• Project Supervision:

  Supervise 12-member student cohorts on

  real-time AI/ML R&D problem statements

  provided by corporate partners (e.g., NLP systems, Computer Vision applications, Predictive Modeling).

• Workflow Coaching:

  Coach students on the

  end-to-end product development lifecycle

  for AI/ML solutions, including data acquisition/cleaning, model design, training, optimization, and production deployment (MLOps).

• Tech Stack Expertise:

  Provide deep technical guidance in core AI/ML technologies:

• Languages:

  Python, R.

• Frameworks:

  TensorFlow, PyTorch, Scikit-learn.

• Cloud:

  AWS/Azure/GCP ML services.

• Concepts:

  Deep Learning (LLMs, GenAI), Reinforcement Learning, Data Engineering principles.

• Quality Assurance:

  Conduct code reviews, architecture critiques, and model validation to ensure projects meet industry standards for scalability, performance, and ethical AI/ML practices.

2. Integrated Learning & Agile Culture

• Agile Integration:

  Work closely with the Junior Scrum Master to embed the

  Agile demands

  of the industrial world, ensuring AI/ML tasks are effectively defined, estimated, and executed within Sprint cycles.

• Professional Competency:

  Guide students on the non-technical but critical aspects of corporate work, including:

• Team Collaboration

  and effective communication within cross-functional teams.

• Workload Distribution

  and navigating project ambiguity.

• Workplace Etiquette

  and the process of giving/receiving professional feedback.

• Mindset Shift:

  Actively cultivate the

  Job-Creator Mindset,

  encouraging students to move beyond theoretical knowledge toward innovation, ownership, and entrepreneurial problem-solving.

3. Operational Oversight & Stakeholder Reporting

• Curriculum Feedback:

  Provide continuous feedback to TrooperCruit on the effectiveness of the

  Integrated Workplace Learning Model

  and suggest adjustments to keep the AI/ML curriculum aligned with rapidly evolving technological advancements.

• Reporting:

  Communicate project status, technical challenges, and student performance metrics to TrooperCruit and corporate stakeholders.

• Batch Supervision:

  For

  Full-Time Mentors

  , take ownership of the overall performance and professional development of assigned student batches, including managing their performance evaluations.

Required Skills & Qualifications

• Experience:

  3 to 6 years

  of hands-on, professional experience in an AI/ML Engineer, Data Scientist, or Applied Research role within a corporate software environment.

• Technical Proficiency:

  Demonstrated expertise in designing, building, and deploying Machine Learning models into production environments. Practical experience with

  Generative AI (LLMs, RAG)

  is highly desirable.

• Coaching Aptitude:

  Proven ability or strong desire to teach, mentor, and simplify complex technical concepts for early-career professionals or students.

• Industry Process Knowledge:

  Practical experience working in an Agile (Scrum/Kanban) development environment.

• Soft Skills:

  High level of emotional intelligence, patience, strong presentation skills, and the ability to inspire and motivate diverse teams.

• Education:

  B.Tech/M.Tech/M.S. in Computer Science, Data Science, or a related field.

Why Partner with TrooperCruit

• Part-Time Flexibility:

  Maintain your corporate career while making a significant, tangible impact on talent development (ideal for individuals seeking career enrichment).

• Impact:

  Directly contribute to solving the

  persistent disconnect

  between academic theory and industry application.

• Innovation:

  Work at the intersection of education, technology, and entrepreneurship in a unique co-creation organizational entity.