- Company Name
- Primis
- Job Title
- Machine Learning Engineer/Researcher
- Job Description
-
**Job Title:** Machine Learning Engineer / Researcher
**Role Summary:**
Design, develop, and deploy AI‑powered creative tools that transform state‑of‑the‑art research into production systems for video, text, images, audio, and 3D media. The role spans deep learning research, computer vision generation, and system engineering to enable real‑time creative workflows for creators worldwide.
**Expectations:**
- Build end‑to‑end pipelines for multi‑modal media generation and refinement.
- Innovate new generative and reasoning methods that generalize across creative domains.
- Translate cutting‑edge research into scalable, low‑latency production services.
- Collaborate closely with researchers, artists, and product teams to iterate on creative toolkits.
**Key Responsibilities:**
1. **Research & Innovation** – Propose and prototype novel generative models (e.g., video, 3D, audio) that outperform existing baselines. Publish findings in top ML venues (NeurIPS, ICML, ICLR, AAAI).
2. **Model Development & Training** – Design, train, evaluate, and fine‑tune deep neural networks using PyTorch or JAX; manage large‑scale GPU/TPU training pipelines.
3. **System Engineering** – Develop real‑time inference engines for video, text, image, audio, and 3D content; implement multi‑stage pipelines with feedback loops.
4. **Computer Vision Integration** – Build CV modules for relighting, grading, camera motion control, and other studio‑grade adjustments within generators.
5. **Deployment & Optimization** – Optimize models for latency, memory, and throughput; deploy on cloud or edge platforms; maintain CI/CD pipelines and model monitoring.
6. **Collaboration & Knowledge Sharing** – Mentor peers, conduct internal workshops, and produce technical documentation and research reports.
**Required Skills:**
- Proficiency in Python, PyTorch, or JAX; experience with distributed training frameworks (Horovod, DeepSpeed).
- Deep understanding of generative models (GANs, VAEs, diffusion, transformers) and modern deep learning architectures.
- Strong background in computer vision techniques and generative media pipelines.
- Solid grasp of mathematics (probability, calculus, linear algebra) and optimization algorithms.
- Experience with version control, CI/CD, Docker/Kubernetes, and cloud GPU/TPU environments.
- Ability to translate research into production‑ready code and conduct rigorous experimentation.
**Required Education & Certifications:**
- PhD in Computer Science, Machine Learning, or related field preferred for research‑centric work; equivalent experience may be considered.
- At minimum, a Bachelor’s or Master’s degree in CS, ML, or a quantitative discipline.
*Note: Sponsorship will be considered for qualified candidates.*
New york city, United states
Hybrid
07-01-2026