Member of Technical Staff (Machine Learning Engineer)

MISSION & MISSION, LLC
Vienna, VA, United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
1 year minimum
Working hours
Regular working hours

Tech stack

Java (Programming Language) Amazon Web Services Big Data C++ (Programming Language) Nvidia CUDA Relational Databases Distributed Computing Environment Memory Management Python (Programming Language) PostgreSQL Machine Learning MySQL
+11 more
Open Source Technology Tensorflow Video Editing Multithreading Cloud Platform System Real Time Systems Pytorch Apache Spark Information Technology Low Latency Machine Learning Operations

Job description

  • 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 and adapt them for product needs
  • Conduct experiments, analyze results, and iterate to improve performance
  • Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale
  • Participate with advancements in machine learning and apply them to continuously improve products What We’re Looking For Required Qualifications

Requirements

  • MS/PhD in Computer Science, Electrical Engineering, or related field
  • Strong research experience with familiarity in top conferences (e.g., CVPR, ICCV, NeurIPS)
  • 5+ years of experience in Python and proficiency in Java, C++, or Scala
  • Strong understanding of diffusion models
  • Strong understanding of multi-threading and memory management
  • Solid knowledge of ML architectures: CNNs and Transformers
  • Experience with PyTorch or TensorFlow
  • Experience building end-to-end ML deployment and inference systems, especially for low-latency, real-time applications
  • Experience deploying ML models in cloud environments (AWS preferred)
  • Experience with experiment tracking systems and ML workflows Nice to Have
  • Experience in low level optimisation, cuda etc.
  • Experience productionizing and scaling ML models in real-world systems
  • Contributions to open-source projects
  • Experience with MLOps tools or distributed training systems
  • Familiarity with relational databases (Postgres/MySQL)
  • Experience handling large-scale data using tools like Spark

About the company

Reka’s mission is to build useful multimodal artificial intelligence and use it to empower organisations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade.

Why Reka?

  • An Elite Team: Collaborate with top-tier engineers, researchers, operators from renowned organizations like Google DeepMind and Facebook AI Research (FAIR) and successful startups, driving innovation in cutting-edge AI technology.
  • Massive Market Opportunity: Be part of a rapidly growing industry poised to transform multiple sectors globally, offering the chance to make a significant impact.
  • Mission-Driven Environment: Work alongside a collaborative, mission-focused team dedicated to advancing AI for meaningful applications.
  • Inclusive and Open Culture: Thrive in an open and inclusive work environment that values diverse perspectives and fosters creativity.
  • Generous Benefits: Enjoy 5 weeks of paid leave to recharge, comprehensive healthcare benefits including vision and dental, and additional perks that support your well-being.
  • Visa Support: We provide visa assistance, including H1B and OPT transfers, for US employees to ensure a smooth transition and support your career with us.

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