Machine Learning Engineer (Inter, Junior, Mid, Senior)

Description

Mandatory: Explore AICINES product at: aicines.com

Immediate Requirement: Referrals encouraged.

Company Description AICines.ai is the world’s first end-to-end AI content creation and monetization platform, built specifically for AI-generated video content from short reels to full-length feature films. The platform unifies AI-driven story and script generation, scene and character creation, smart editing tools, hosting, and revenue monetization in a single ecosystem. By redefining the entertainment pipeline from script to screen through multimodal intelligence, AICines.ai empowers creators, brands, and studios to produce cinematic content at scale. Operating at the intersection of AI, FilmTech, and the creator economy, the company is focused on building the next generation of AI-powered storytelling for a global audience.

Open to interns, fresh graduates, and early-career professionals — we hire based on what you can do, not your job title or years of experience.

Responsibilities

Mandatory: Explore AICINES product at: aicines.com

Immediate Requirement: Referrals encouraged.

Role Description The Machine Learning Engineer role at AICines.ai is a remote position focused on building and optimizing the AI models that power story, scene, and character generation across the platform. On a day-to-day basis, this role involves training and fine-tuning generative models, improving inference performance, and integrating ML pipelines into production systems. The engineer will collaborate with research and product teams to push the boundaries of multimodal AI, evaluate model quality, and help scale AI-powered content generation to a global audience.

Requirements

Mandatory: Explore AICINES product at: aicines.com

Qualifications

Experience with machine learning frameworks such as PyTorch or TensorFlow.

Understanding of generative models (e.g., diffusion models, LLMs, GANs) and multimodal AI.

Experience deploying ML models into production and optimizing inference performance.

Strong programming skills in Python and familiarity with ML infrastructure/MLOps practices.

Ability to read and apply research papers to practical engineering problems.

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.