ML Engineering Intern Full Time NEW

Company Description

Laser Labs is a cutting-edge AI and software venture studio dedicated to building intelligent products in automation, analytics, and productivity. Operating with a lab-like mindset, the organization emphasizes rapid experimentation, idea validation, and delivering impactful software solutions across diverse industries. With a small and agile team, Laser Labs fosters ownership, learning, and direct user engagement, empowering individuals to make a meaningful impact from day one. Join us if you’re ready to innovate, learn quickly, and create transformative products.

Role Description

This is a full-time, on-site internship role for a Machine Learning Engineering Intern based in India. The Intern will assist in designing, implementing, and evaluating machine learning models to power intelligent products. Responsibilities include data preprocessing, developing algorithms, collaborating with cross-functional teams, conducting experiments, and improving the accuracy and efficiency of systems. Extend and debug an existing Jupyter-based ML pipeline (Python/Jupyter Lab environment). The Intern will also gain hands-on exposure to cutting-edge ML technologies and contribute actively to product development from ideation to deployment.

Qualifications

• Knowledge of Machine Learning fundamentals, data preprocessing, and model evaluation
• Proficiency in programming languages such as Python and libraries like TensorFlow or PyTorch
• Understanding of data analytics and experience working with large datasets
• Strong problem-solving, critical thinking, and algorithm design skills
• Ability to collaborate effectively with cross-functional teams and communicate technical concepts clearly
• Pursuing or recently completed a degree in Computer Science, Data Science, Engineering, or a related field
• Passion for innovation, fast learning, and contributing to meaningful projects
• Previous experience in AI/ML projects or internships is a plus

Nice to Have

– Experience with recommendation systems, collaborative filtering, or user behavior modeling

– Familiarity with REST APIs or Flask/FastAPI for model serving

– Comfort with cloud infrastructure (AWS, GCP, or similar)

Compensation

Paid — rate commensurate with experience. Project-based or hourly, flexible.

To Apply

Send your resume, your GitHub or any relevant project links, and 2–3 sentences on a model you’ve built from scratch.