About the job

ML Engineer (Studio Applications)

Location: Remote (India)

Level: Mid/Senior (5–10+ years)

About the role

The ML Engineer (Studio Applications) focuses on deploying and maintaining machine learning models that support LoglineAI’s production workflows. The role is primarily applied and production-focused rather than research-oriented.

The engineer will integrate third-party and open-source models for image and video generation, enhancement, and quality control into the platform. They will fine-tune models where necessary, manage inference services, and work with pipeline engineers and any research staff to ensure models perform reliably in real use cases.

Responsibilities:
Integrate third-party and open-source models (image/video generation, super-resolution, artifact detection) into LoglineAI’s platform.
Fine-tune or adapt models for specific needs such as style preservation, character identity, motion and camera control, and cleanup.
Design and operate inference services, including model serving, autoscaling, A/B testing,



and performance monitoring.
Collaborate with Pipeline Engineers on model selection, parameter choices, and trade-offs between cost and quality.
Work with research-oriented staff to convert prototypes into secure, monitored production services.

Requirements:
5–10+ years of experience in machine learning or computer vision, with robust Python and PyTorch/TensorFlow skills.
Proven experience deploying models to production (batch or real-time inference).
Experience with diffusion or other generative models, ideally including video or sequence-aware work.
Familiarity with Docker/Kubernetes, experiment tracking (e.g., Weights & Biases, MLflow), and ML observability practices.
Ability to read and implement methods from research papers at a practical level.

Ideal Candidate comes from applied CV/ML product teams or ML platform/MLOps settings, working in Machine Learning Engineer, Computer Vision Engineer, Appl

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