The Role
Leads the company’s machine learning research and development strategy, focusing on multimodal generative models for video, audio, and language. Designs architectures and large-scale training pipelines, builds and mentors a high-performing ML team, and drives deployment of research innovations into production. Collaborates with product, engineering, and creative teams, establishes ML standards, evaluates emerging technologies, and represents the company through research publications and conferences.
Summary Generated by Built In
The Head of Machine Learning will lead our research and development efforts in generative models with a main focus on multimodal generation, with main focus on video generation but also audio, and language-based models.This strategic leadership position sits at the intersection of technical expertise and organizational vision, requiring both hands-on experience with generative models and the ability to guide teams toward breakthrough results. You will be responsible for designing ML architectures and training pipelines, building and managing a skilled technical team, and ensuring research innovations can be successfully implemented in production environments, audio integration, and language model applications. This includes building systems that coordinate multimodal
inputs—visual, auditory, and textual—to enable rich, realistic, and controllable outputs for creative and production workflows.
inputs—visual, auditory, and textual—to enable rich, realistic, and controllable outputs for creative and production workflows.
Key Responsibilities / Job Duties
Research & Development Leadership
● Define and execute the strategic roadmap for generative ML research aligned with company
objectives
● Lead research initiatives in multimodal generative models (video, audio, language), temporal
consistency techniques, and multimodal generation with main focus on video generation
● Design and optimize large-scale training and fine-tuning pipelines for generative models
● Drive innovation in ML architecture, evaluation methodologies, and performance optimization
● Balance scientific experimentation with practical business outcomes.
Team Building & Development
● Build, lead, and mentor a diverse, high-performing ML team
● Establish clear performance metrics, career development paths, and growth opportunities for team
members
members
● Foster a collaborative culture that encourages knowledge sharing, creative problem-solving, and
continuous learning
continuous learning
● Recruit and retain top ML talent through effective leadership and compelling technical challenges
Cross-Functional Collaboration
● Partner with product, engineering, and creative teams to integrate ML innovations into production
systems
● Translate complex ML concepts into accessible terms for non-technical stakeholders● Balance research ambitions with practical business needs and timeline constraints
Technical Strategy & Vision
● Contribute to the company's overall technical and product strategy
● Evaluate emerging technologies and methodologies for potential adoption
● Establish technical standards and best practices for ML development
● Engage with the external research community through publications, conferences, and collaboration
Technical Strategy & Vision
● Contribute to the company's overall technical and product strategy
● Evaluate emerging technologies and methodologies for potential adoption
● Establish technical standards and best practices for ML development
● Engage with the external research community through publications, conferences, and collaboration
Job Requirements / Must Haves
● Exceptional leadership, mentorship, and communication skills.
● Proven track record in leading machine learning R&D teams or projects.
● Advanced degree in Computer Science, Machine Learning, AI, or a related field.
● Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and programming
languages (e.g., Python).
● Deep understanding of AI ethics, fairness, and interpretability.
● Strategic thinking with the ability to define and communicate a compelling vision
Additional Skills / Nice to Have
● PhD and/or strong portfolio of published research and patents in top AI conferences and journals.
● Experience deploying large-scale machine learning models in production.
● Familiarity with cloud platforms and MLOps best practices.
● Proficiency in languages beyond Python, such as C++.
● Able to knit together a high performing distributed team and communicate a consistent vision.
About You
● Visionary thinker with a passion for advancing the state-of-the-art in AI.
● Collaborative and team-oriented.
● Resilient and adaptable in a fast-paced environment.
● High level of curiosity and commitment to continuous learning.
Skills Required
- Exceptional leadership, mentorship, and communication skills
- Proven track record leading machine learning R&D teams or projects
- Advanced degree in Computer Science, Machine Learning, AI, or a related field
- Extensive experience with deep learning frameworks such as TensorFlow or PyTorch
- Extensive experience with programming languages such as Python
- Deep understanding of AI ethics, fairness, and interpretability
- Strategic thinking and ability to define and communicate a compelling vision
- PhD or strong portfolio of published research and patents in top AI conferences and journals
- Experience deploying large-scale machine learning models in production
- Familiarity with cloud platforms and MLOps best practices
- Proficiency in programming languages beyond Python, such as C++
- Ability to build and lead a high-performing distributed team
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The Company
What We Do
BRAHMA AI is an enterprise AI content platform that enables organizations to create, manage, and distribute AI-driven media with intelligence, security, and efficiency. Formed through the integration of Prime Focus Technologies and Metaphysic, it combines CLEAR®, CLEAR® AI, ATMAN digital humans, and VAANI voice localization into one ecosystem. Guided by its Mind² philosophy, BRAHMA AI helps enterprises scale content creation, protect IP, and govern assets with provenance, consent, and trust.
