The Machine Learning Engineer will translate cutting-edge research into production-ready machine learning systems, designing, building, and deploying end-to-end ML models and pipelines.

In Short

Translate cutting-edge research into production-ready machine learning systems
Design, build, and deploy end-to-end ML models and pipelines
Develop and optimize models for image and video processing
Own the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deployment
Rapidly prototype using open-source models
Conduct experiments, analyze results, and iterate to improve performance
Collaborate with researchers and cross-functional teams to deliver ML solutions
Participate with advancements in machine learning to improve products

Requirements

MS/PhD in Computer Science, Electrical Engineering, or related field
5+ years of experience in Python and proficiency in Java, C++, or Scala
Strong research experience with familiarity in top conferences
Strong understanding of diffusion models
Solid knowledge of ML architectures: CNNs and Transformers
Experience with PyTorch or TensorFlow
Experience deploying ML models in cloud environments (AWS preferred)
Experience building end-to-end ML deployment systems

Benefits

Opportunity to work on cutting-edge technology
Collaborative work environment
Flexible working hours
Professional development opportunities

Reka

Reka is a globally distributed foundation model startup headquartered in the San Francisco Bay Area, California, dedicated to building useful multimodal artificial intelligence to empower organizations and businesses. With a remote-first approach, Reka brings together top talent from around the world, including contributors to significant AI breakthroughs over the past decade. The company fosters a collaborative, mission-driven environment focused on advancing AI for meaningful applications, while promoting an inclusive culture that values diverse perspectives. Reka offers generous benefits and is positioned in a rapidly growing industry with massive market opportunities.

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