Sr Machine Learning Engineer (MLOps Focused)
Join our team and shape the future of AI and video creation
We are building the world’s most capable foundational models, allowing anyone to generate beautiful, cinematic and high-definition video in minutes.
We’re a small team of young & hungry researchers, and have raised over $30m from world class investors including Khosla Ventures & YCombinator. We released our first model two months ago, quickly becoming the fastest growing AI product on Discord since Midjourney with over 100,000 users in 6 weeks.
We’re looking for a Sr Machine Learning Engineer and the role is fully remote.
At Moonvalley, our product development process will be a bit non-standard and consist of small autonomous teams working to ship great features and experiences. Here is a good primer. You’ll work closely with your team (product designer, developers) daily, take ownership, make calls, and see things through without a lot of oversight.
What you'll do (responsibilities)
As a Sr Machine Learning Engineer, you'll play a crucial role in developing and maintaining various AI models and features in our software products. You'll work closely with product designers, developers, and other cross-functional teams to deliver high-quality AI-powered solutions.
We're seeking a talented Sr Machine Learning Engineer with a focus on Computer Vision to join our remote team. You should be comfortable working in a remote team environment and have excellent communication skills.
Here are some examples of projects you might work on as a Sr Machine Learning Engineer at our company:
Implement CI/CD pipelines for machine learning models.
Contribute to R&D projects aimed at developing computer vision models.
Collaborate with Engineers to manage data ingestion, validation, and ML feature stores.
Collaborating with cross-functional teams to define, design, and implement machine learning models and pipelines.
Collaborate in developing frameworks for testing and validating machine learning models at scale.
Participate in swift iteration cycles related to Training/Fine-Tuning, testing and deployment of models.
Maintain and monitor deployed models, ensuring their robustness and scalability.
Communicating clearly and effectively with cross-functional teams to understand requirements and provide technical guidance.
We value team players who are passionate about their work and continuously strive for personal and professional growth. If you're excited about the prospect of joining a dynamic team and making a meaningful impact on our products, we encourage you to apply.
What we're looking for (qualifications)
To be considered for this position, you should have:
3+ years of experience in Machine Learning Operations (MLOps).
Proficiency in cloud platforms, specifically AWS and its MLOps services (SageMaker, CodePipeline).
Exceptionally strong Python skills - Minimum 5 years of experience
Knowledge of CNN, RNN/LSTM/GRU, and Transformer models
Knowledge of containerization technologies like Docker and Kubernetes.
Experience deploying ML models in the Cloud
Familiarity with Data Version Control (DVC) and other machine learning lifecycle tools.
Experience with databases (Postgres/MySQL)
ML framework: Pytorch / Tensorflow
Experience with experiment tracking systems
What we offer (compensation & benefits)
Competitive salary and equity
Unlimited paid vacation
Fully-distributed culture that’s async first
How to apply
This is a fully remote position with Moonvalley, and we welcome candidates from anywhere. However, we require that you have an overlap with the rest of the team based in MENA and North America working hours.
If you're excited about the opportunity to work on cutting-edge AI technology and help shape the future of video content creation, we encourage you to apply. We look forward to hearing from you!
The statements contained in this job description reflect general details as necessary to describe the principal functions of this job, the level of knowledge and skill typically required and the scope of responsibility. It should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned, including work in other functional areas to cover absences, to equalize peak work periods, or to otherwise balance organizational work