Apprentice-IT
What you'll do:
We are looking for a motivated AI/ML Engineering graduate to join our Artificial Intelligence and Machine Learning (AIML) team. This role is ideal for a fresher with a strong academic foundation in AI/ML who is eager to apply theory to real world business problems under mentorship.
You will work closely with senior AI/ML engineers, data scientists, and platform teams to build, experiment with, and operationalize machine learning solutions on enterprise scale data platforms.
• Assist in building and training machine learning models for structured and unstructured data use cases
• Perform data analysis, preprocessing, and feature engineering on large datasets
• Support experimentation using AutoML and custom ML approaches
• Evaluate model performance and assist in tuning for accuracy and robustness
• Work with AI/ML platforms and tools for model development and experimentation
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• Collaborate with engineers and analysts to understand business problems and translate them into ML tasks
• Document experiments, learnings, and model outcomes clearly
• Follow best practices for responsible AI, data governance, and security
Qualifications:
• Bachelor's degree in Engineering (B.E./B.Tech) with specialization in:
o Artificial Intelligence
o Machine Learning
o Data Science
o Computer Science (with strong AI/ML coursework)
Skills:
• Strong fundamentals in:
o Machine Learning algorithms
o Statistics and linear algebra
o Data structures and basic algorithms
• Working knowledge of Python
• Familiarity with ML libraries such as:
o scikit learn
o TensorFlow or PyTorch (basic exposure is sufficient)
• Basic understanding of SQL and working with datasets
Good to Have (Not Mandatory)
• Exposure to:
o Cloud platforms (Azure / AWS / GCP)
o Data platforms like Snowflake
o ML lifecycle concepts (training, evaluation, deployment)
• Academic or personal projects involving:
o Predictive modeling
o NLP or computer vision
o Time series forecasting
• Familiarity with notebooks, Git, or basic MLOps concepts
What You Will Learn
• End to end AI/ML use case development in an enterprise environment
• Working with real production scale datasets
• Model experimentation, evaluation, and promotion practices
• AI/ML platform tools and best practices
• How ML solutions are governed, monitored, and scaled
Perks and Benefits
Health and Wellness
- Health Insurance
- Health Reimbursement Account
- Dental Insurance
- Vision Insurance
- Life Insurance
- Short-Term Disability
- Long-Term Disability
- FSA
- HSA With Employer Contribution
- Fitness Subsidies
- On-Site Gym
- Pet Insurance
- Mental Health Benefits
- Virtual Fitness Classes
Parental Benefits
- Birth Parent or Maternity Leave
- Adoption Assistance Program
Work Flexibility
- Flexible Work Hours
- Remote Work Opportunities
- Hybrid Work Opportunities
Office Life and Perks
- Casual Dress
- On-Site Cafeteria
Vacation and Time Off
- Paid Vacation
- Paid Holidays
- Personal/Sick Days
- Leave of Absence
- Summer Fridays
Financial and Retirement
- 401(K) With Company Matching
- Performance Bonus
- Relocation Assistance
- Financial Counseling
Professional Development
- Tuition Reimbursement
- Promote From Within
- Mentor Program
- Shadowing Opportunities
- Access to Online Courses
- Internship Program
- Work Visa Sponsorship
- Leadership Training Program
- Associate or Rotational Training Program
Diversity and Inclusion
- Diversity, Equity, and Inclusion Program
- Employee Resource Groups (ERG)