MLOps Intern (Remote | US Time Zone)
Internship Terms (Non-Negotiable)
- Initial 2 Months: Unpaid, performance-based evaluation period
- Following 4 Months: Paid internship strictly based on performance
- Full-Time Conversion: Possible only for top performers
- Failure to meet expectations during the evaluation period will result in immediate termination
Work Schedule
- Remote role
- Mandatory availability during US working hours
- Daily stand-ups and weekly performance reviews are compulsory
Core Responsibilities
- Design, build, and maintain end-to-end MLOps pipelines
- Implement and manage Apache Airflow DAGs in production
- Automate ML workflows including data ingestion, training, validation, deployment, and monitoring
- Handle failures, retries, and pipeline optimizations without supervision
- Work with stock market and options trading data
- Ensure reproducibility, versioning, and monitoring of ML models
- Maintain clean, production-ready code and detailed documentation
Mandatory Requirements (No Exceptions)
Candidates must already have:
- Strong hands-on experience with Apache Airflow
- Advanced Python proficiency (data pipelines, automation, scripting)
- Clear understanding of MLOps lifecycle (CI/CD, model versioning, drift detection)
- Working knowledge of Docker and Linux environments
- Familiarity with cloud platforms (AWS / GCP / Azure)
- Solid understanding of options trading, derivatives, and stock market mechanics
- Experience using Git in team environments
- Ability to debug issues independently and meet strict deadlines
Note: Candidates who only know theory or have done online courses only should not apply.
Eligibility Criteria
- Graduates only (Computer Science, Engineering, Data Science, or related fields)
- Strong analytical thinking and problem-solving ability
- Excellent written and verbal communication
- High ownership mindset and ability to work with minimal guidance
What This Role Is NOT
- Not a training program
- Not a beginner internship
- Not suitable for part-time availability
- Not flexible with working hours or deadlines
What We Offer
- Exposure to real production systems
- High-pressure, high-learning environment
- Paid internship after evaluation period
- Potential full-time offer for exceptional performers
Application Process:
Submit your resume along with:
- Links to GitHub / Airflow projects
- Brief explanation of your MLOps experience
- Proof of stock market or options trading knowledge
Only shortlisted candidates will be contacted.
